We revisit the problem of real-time verification with dense time dynamics using timeout and calen... more We revisit the problem of real-time verification with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a finite state verification problem. To overcome the complexity of verification of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and verified safety properties using k-induction in association with bounded model checking. In this work, we introduce a specification formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verification of qualitative temporal properties on infinite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless finite state models through a two-step process comprising of digitization and canonical finitary reduction. This technique enables us to verify safety invariants for real-time systems using finite state model-checking avoiding the complexity of infinite state (bounded) model checking and scale up models without applying techniques from induction based proof methodology. Moreover, we can verify liveness properties for real-time systems, which is not possible by using induction with infinite state model checkers. We present examples of Fischer's Protocol, Train-Gate Controller, and TTA start-up algorithm to illustrate how such an approach can be efficiently used for verifying safety, liveness, and timeliness properties specified in LTL using finite state model checkers like SAL-smc and Spin. We also demonstrate how advanced modeling concepts like inter-process scheduling, priorities, interrupts, urgent and committed location can be specified as extensions of the proposed specification formalism, that can be subjected to the proposed two step reduction technique for verification purposes.
Software Testing, Verification & Reliability, Oct 10, 2016
We revisit the problem of real-time verification with dense time dynamics using timeout and calen... more We revisit the problem of real-time verification with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a finite state verification problem. To overcome the complexity of verification of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and verified safety properties using k-induction in association with bounded model checking. In this work, we introduce a specification formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verification of qualitative temporal properties on infinite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless finite state models through a two-step process comprising of digitization and canonical finitary reduction. This technique enables us to verify safety invariants for real-time systems using finite state model-checking avoiding the complexity of infinite state (bounded) model checking and scale up models without applying techniques from induction based proof methodology. Moreover, we can verify liveness properties for real-time systems, which is not possible by using induction with infinite state model checkers. We present examples of Fischer's Protocol, Train-Gate Controller, and TTA start-up algorithm to illustrate how such an approach can be efficiently used for verifying safety, liveness, and timeliness properties specified in LTL using finite state model checkers like SAL-smc and Spin. We also demonstrate how advanced modeling concepts like inter-process scheduling, priorities, interrupts, urgent and committed location can be specified as extensions of the proposed specification formalism, that can be subjected to the proposed two step reduction technique for verification purposes.
We revisit the problem of real-time verification with dense time dynamics using timeout and calen... more We revisit the problem of real-time verification with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a finite state verification problem. To overcome the complexity of verification of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and verified safety properties using k-induction in association with bounded model checking. In this work, we introduce a specification formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verification of qualitative temporal properties on infinite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless finite state models through a two-step process comprising of digitization and canonical finitary reduction. This technique enables us to verify safety invariants for real-time systems using finite state model-checking avoiding the complexity of infinite state (bounded) model checking and scale up models without applying techniques from induction based proof methodology. Moreover, we can verify liveness properties for real-time systems, which is not possible by using induction with infinite state model checkers. We present examples of Fischer's Protocol, Train-Gate Controller, and TTA start-up algorithm to illustrate how such an approach can be efficiently used for verifying safety, liveness, and timeliness properties specified in LTL using finite state model checkers like SAL-smc and Spin. We also demonstrate how advanced modeling concepts like inter-process scheduling, priorities, interrupts, urgent and committed location can be specified as extensions of the proposed specification formalism, that can be subjected to the proposed two step reduction technique for verification purposes.
Findings of the Association for Computational Linguistics: EMNLP 2021, 2021
Robust sequence-to-sequence modelling is an essential task in the real world where inputs are oft... more Robust sequence-to-sequence modelling is an essential task in the real world where inputs are often noisy. Both user-generated and machine generated inputs contain various kinds of noises in the form of spelling mistakes, grammatical errors, character recognition errors etc, all of which impact downstream tasks and affect interpretability of texts. In this work, we devise a novel sequence-to-sequence architecture for detecting and correcting different real world and artificial noises (adversarial attacks) from English texts. Towards that we propose a modified transformer-based encoderdecoder architecture that uses a gating mechanism to detect types of corrections required and accordingly corrects texts. Experimental results show that our gated architecture with pre-trained language models perform significantly better that the non-gated counterparts and other state-of-the-art error correction models in correcting spelling and grammatical errors. Extrinsic evaluation of our model on Machine Translation (MT) and Summarization tasks show the competitive performance of the model against other generative sequence-tosequence models under noisy inputs. * The author was employed at Optum Global Advantage, India during the entire work.
Time-triggered architectures form the important component of many distributed computing platforms... more Time-triggered architectures form the important component of many distributed computing platforms for safetycritical real-time applications such as avionics and automotive control systems. TTA, FlexRay and TTCAN are examples of such time-triggered architectures that have been popular in recent times. These architectures involve a number of algorithms for synchronizing a set of distributed computing nodes for meaningful exchange of data among themselves. The algorithms include a startup algorithm whose job is to integrate one or more nodes into the group of communicating nodes. The startup algorithm runs on every node when the system is powered up, and again after a failure occurs. Some critical issues need to be considered in the design of the startup algorithms, for example, the algorithms should be robust under reasonable assumptions of failures of nodes and channels. The safety-critical nature of the applications where these algorithms are used demand rigorous verification of these algorithms and there have been numerous attempts to use formal verification techniques for this purpose. This paper focuses on various formal verification efforts carried out for ensuring the correctness of the startup algorithms. In particular, the verification of different startup algorithms used in three time-triggered architectures, TTA, FlexRay and TTCAN, are studied, compared and contrasted. Besides presenting the various verification approaches for these algorithms, the gaps and possible improvements on the verification efforts are also indicated.
In this work we propose techniques for efficient reachability analysis of the state space (e.g., ... more In this work we propose techniques for efficient reachability analysis of the state space (e.g., detection of bad states) using a combination of partial order and symmetry based reductions in a distributed setting. The proposed techniques are focused towards explicit state space enumeration based model-checkers like SPIN. We consider variants for both depth-first as well as breadth-first based generation of the reduced state graphs on-the-fly.
Short text is a popular avenue of sharing feedback, opinions and reviews on social media, e-comme... more Short text is a popular avenue of sharing feedback, opinions and reviews on social media, e-commerce platforms, etc. Many companies need to extract meaningful information (which may include thematic content as well as semantic polarity) out of such short texts to understand users’ behaviour. However, obtaining high quality sentiment-associated and human interpretable themes still remains a challenge for short texts. In this paper we develop ELJST, an embedding enhanced generative joint sentiment-topic model that can discover more coherent and diverse topics from short texts. It uses Markov Random Field Regularizer that can be seen as generalisation of skip-gram based models. Further, it can leverage higher order semantic information appearing in word embedding, such as self-attention weights in graphical models. Our results show an average improvement of 10% in topic coherence and 5% in topic diversification over baselines. Finally, ELJST helps understand users’ behaviour at more gr...
Business process models expressed in languages such as BPMN (Business Process Model and Notation)... more Business process models expressed in languages such as BPMN (Business Process Model and Notation), play a critical role in implementing the workflows in modern enterprises. However, control flow errors such as deadlocks and lack of synchronization, and syntactic errors arising out of poor modeling practices often occur in industrial process models. A major challenge is to provide the means and methods to detect such errors and more importantly, to identify the location of each error. In this work, we develop a formal framework of diagnosing errors by locating their occurrence nodes in business process models at the level of sub-processes and swim-lanes. We use graph-theoretic techniques and Petri net-based analyses to detect syntactic and control flow-related errors respectively. While syntactic errors can be easily located on the processes themselves, we project control-related errors on processes using a mapping from Petri nets to processes. We use this framework to analyze a samp...
Ticketing system is an example of a Service System (SS) which is responsible for handling huge vo... more Ticketing system is an example of a Service System (SS) which is responsible for handling huge volumes of tickets generated by large enterprise IT (Information Technology) infrastructure components, and ensuring smooth operation. The system maintains the provision of recording the time that reflects when a ticket is opened, acknowledged to user, resolved and/or closed, from which different QoS parameters could be obtained. For example, Resolution Time can be computed as the difference of resolution date and opening date of the ticket. One needs to use new technology solutions in QoS-related analysis like categorization of tickets according to their QoS, predicting QoS parameters for new tickets etc., to improve the performance of the SS. In this work we propose boosting oriented solutions to QoS prediction of tickets using crisp and fuzzy set models of QoS. In particular, we employ a two-stage analysis framework for QoS prediction for incoming tickets which includes clustering incid...
We revisit the problem of real-time verication with dense time dynamics using timeout and calenda... more We revisit the problem of real-time verication with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a nite state verication problem. To overcome the complexity of verication of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and veried safety properties using k-induction in association with bounded model checking. In this work, we introduce a specication formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verication of qualitative temporal properties on innite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless nite state models through a two-step process comprising of digitization and ...
A semantic annotation of business processes with concepts from ontology has become necessity in s... more A semantic annotation of business processes with concepts from ontology has become necessity in service provisioning. There have been few work on semantically labeling business processes in terms of ontology that formalizes business process structure, business domains etc. However, dynamic behavior of a process cannot be captured by such means as ontology languages are not suitable for specifying behavioral semantics. In this work, we propose a method for labeling and specifying business processes by using hybrid programs as the knowledge representation formalism. The formalism of hybrid programs integrates normal programs (using the parlance of logic programming) with ontology specified in OWL-DL (semantic web standard).
Several methods on simultaneous detection of sentiment and topics have been proposed to obtain su... more Several methods on simultaneous detection of sentiment and topics have been proposed to obtain subjective information such as opinion, attitude and feelings expressed in texts. Most of the techniques fail to produce desired results for short texts. In this paper, we propose LJST, a labeled joint sentiment-topic model particularly for short texts. It uses a probabilistic framework based on latent Dirichlet allocation. LJST is semi-supervised-it predicts the sentiment values for unlabeled texts in presence of a partially labeled texts with sentiment values. To address the sparsity problem in short text, we modify LJST and introduce Bi-LJST, which uses bi-terms (all possible pairs of words in a document) in place of unigrams for learning the topics by directly generating word co-occurrence patterns in each text and expressing the topics in terms of these patterns. Specifically, we have proposed a semi-supervised approach of extracting joint sentiment-topic model for short texts by incorporating bi-terms. Extensive experiments on three real-world datasets show that our methods perform consistently better than three other baselines in terms of document-level and topic-level sentiment prediction, and topic discovery-LJST using bi-term models outperforms the best baseline by producing 12% lower RMSE for document-level sentiment prediction and 6% higher F1 score for topic-sentiment prediction.
Process modeling forms a core activity in many organizations in which different entities and stak... more Process modeling forms a core activity in many organizations in which different entities and stakeholders interact for smooth operation and management of enterprises. There have been few work on semantically labeling business processes using OWL-DL that formalize business process structure and query them. However, all these methods suffer from few limitations such as lack of a modular approach of ontology design, no guarantee of a consistent ontology development with TBox and ABox axioms and no provision of combining control flow relations of the main process and its sub-processes. In this work, we propose an approach for labeling and specifying business processes by using hybrid programs which offers modular ontology design, consistent ontology design of each module and unified control flow for process and its sub-processes. This formalism of hybrid programs integrates ontology specified in OWL-DL with SWRL (Semantic Web Rules Language) rules. Further we report on our experimental effort on modeling industrial business processes with this hybrid formalism. We also present a case study of an industrial business process to illustrate our modeling approach which can aid in business knowledge management.
The goal of a Service System in an organization is to deliver uninterrupted service towards achie... more The goal of a Service System in an organization is to deliver uninterrupted service towards achieving business success. Ticketing system is an example of a Service System which is responsible for handling huge volumes of tickets generated by large enterprise IT (Information Technology) infrastructure components and ensuring smooth operation. Instead of manual screening one needs to extract information automatically from them to gain insights to improve operational efficiency. To ensure better operation we propose a framework to cluster incident tickets based on their textual context that can eliminate manual classification of them, which is labor intensive and costly. Further we label each of the clusters by generating meaningful keywords as logical itemsets, extracting candidate labels from Wikipedia articles, and finally scoring each of labels against each cluster. These labels can reflect an adequate and concise specification of each cluster. Further we experiment our approach with industrial ticket data from three different domains and report on the learned experience. We believe that our framework for clustering and labeling will enable enterprises to prioritize the issues in their IT infrastructure and improve the reliability and availability of their services.
2016 IEEE International Conference on Services Computing (SCC), 2016
These days IT service providers are rapidly embracing an automated services delivery model in ord... more These days IT service providers are rapidly embracing an automated services delivery model in order to keep pace with advances in technology and demanding market pressure to reduce and maintain quality. Application development and maintenance is a good example of a service system in which a sizable volume of tickets are raised everyday for different issues to get resolved with a view to deliver uninterrupted service. An issue is captured as summary on the ticket and once a ticket is resolved, the solution is also noted down on the ticket as resolution. It will be beneficial to automatically extract information from the description of tickets to improve operations like identifying critical and frequent issues, grouping of tickets based on textual content, suggesting remedial measures for them etc. In particular, the maintenance people can save a lot of effort and time if they have access to past remedial actions for similar kind of tickets raised earlier based on history data. In this work we propose an automated method based on background knowledge of tickets for recovering resolutions for fresh tickets using unsupervised learning and the traditional kNN (k-nearest neighbor) search. In absence of domain ontology we use ticket description to extract ontology which is grounded in WordNet. The experiment of our dataset shows that we are able to achieve a promising similarity match of about 48% between the suggestions and the actual resolution which shows an improvement over clustering without background knowledge.
We revisit the problem of real-time verification with dense time dynamics using timeout and calen... more We revisit the problem of real-time verification with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a finite state verification problem. To overcome the complexity of verification of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and verified safety properties using k-induction in association with bounded model checking. In this work, we introduce a specification formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verification of qualitative temporal properties on infinite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless finite state models through a two-step process comprising of digitization and canonical finitary reduction. This technique enables us to verify safety invariants for real-time systems using finite state model-checking avoiding the complexity of infinite state (bounded) model checking and scale up models without applying techniques from induction based proof methodology. Moreover, we can verify liveness properties for real-time systems, which is not possible by using induction with infinite state model checkers. We present examples of Fischer's Protocol, Train-Gate Controller, and TTA start-up algorithm to illustrate how such an approach can be efficiently used for verifying safety, liveness, and timeliness properties specified in LTL using finite state model checkers like SAL-smc and Spin. We also demonstrate how advanced modeling concepts like inter-process scheduling, priorities, interrupts, urgent and committed location can be specified as extensions of the proposed specification formalism, that can be subjected to the proposed two step reduction technique for verification purposes.
Software Testing, Verification & Reliability, Oct 10, 2016
We revisit the problem of real-time verification with dense time dynamics using timeout and calen... more We revisit the problem of real-time verification with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a finite state verification problem. To overcome the complexity of verification of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and verified safety properties using k-induction in association with bounded model checking. In this work, we introduce a specification formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verification of qualitative temporal properties on infinite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless finite state models through a two-step process comprising of digitization and canonical finitary reduction. This technique enables us to verify safety invariants for real-time systems using finite state model-checking avoiding the complexity of infinite state (bounded) model checking and scale up models without applying techniques from induction based proof methodology. Moreover, we can verify liveness properties for real-time systems, which is not possible by using induction with infinite state model checkers. We present examples of Fischer's Protocol, Train-Gate Controller, and TTA start-up algorithm to illustrate how such an approach can be efficiently used for verifying safety, liveness, and timeliness properties specified in LTL using finite state model checkers like SAL-smc and Spin. We also demonstrate how advanced modeling concepts like inter-process scheduling, priorities, interrupts, urgent and committed location can be specified as extensions of the proposed specification formalism, that can be subjected to the proposed two step reduction technique for verification purposes.
We revisit the problem of real-time verification with dense time dynamics using timeout and calen... more We revisit the problem of real-time verification with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a finite state verification problem. To overcome the complexity of verification of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and verified safety properties using k-induction in association with bounded model checking. In this work, we introduce a specification formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verification of qualitative temporal properties on infinite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless finite state models through a two-step process comprising of digitization and canonical finitary reduction. This technique enables us to verify safety invariants for real-time systems using finite state model-checking avoiding the complexity of infinite state (bounded) model checking and scale up models without applying techniques from induction based proof methodology. Moreover, we can verify liveness properties for real-time systems, which is not possible by using induction with infinite state model checkers. We present examples of Fischer's Protocol, Train-Gate Controller, and TTA start-up algorithm to illustrate how such an approach can be efficiently used for verifying safety, liveness, and timeliness properties specified in LTL using finite state model checkers like SAL-smc and Spin. We also demonstrate how advanced modeling concepts like inter-process scheduling, priorities, interrupts, urgent and committed location can be specified as extensions of the proposed specification formalism, that can be subjected to the proposed two step reduction technique for verification purposes.
Findings of the Association for Computational Linguistics: EMNLP 2021, 2021
Robust sequence-to-sequence modelling is an essential task in the real world where inputs are oft... more Robust sequence-to-sequence modelling is an essential task in the real world where inputs are often noisy. Both user-generated and machine generated inputs contain various kinds of noises in the form of spelling mistakes, grammatical errors, character recognition errors etc, all of which impact downstream tasks and affect interpretability of texts. In this work, we devise a novel sequence-to-sequence architecture for detecting and correcting different real world and artificial noises (adversarial attacks) from English texts. Towards that we propose a modified transformer-based encoderdecoder architecture that uses a gating mechanism to detect types of corrections required and accordingly corrects texts. Experimental results show that our gated architecture with pre-trained language models perform significantly better that the non-gated counterparts and other state-of-the-art error correction models in correcting spelling and grammatical errors. Extrinsic evaluation of our model on Machine Translation (MT) and Summarization tasks show the competitive performance of the model against other generative sequence-tosequence models under noisy inputs. * The author was employed at Optum Global Advantage, India during the entire work.
Time-triggered architectures form the important component of many distributed computing platforms... more Time-triggered architectures form the important component of many distributed computing platforms for safetycritical real-time applications such as avionics and automotive control systems. TTA, FlexRay and TTCAN are examples of such time-triggered architectures that have been popular in recent times. These architectures involve a number of algorithms for synchronizing a set of distributed computing nodes for meaningful exchange of data among themselves. The algorithms include a startup algorithm whose job is to integrate one or more nodes into the group of communicating nodes. The startup algorithm runs on every node when the system is powered up, and again after a failure occurs. Some critical issues need to be considered in the design of the startup algorithms, for example, the algorithms should be robust under reasonable assumptions of failures of nodes and channels. The safety-critical nature of the applications where these algorithms are used demand rigorous verification of these algorithms and there have been numerous attempts to use formal verification techniques for this purpose. This paper focuses on various formal verification efforts carried out for ensuring the correctness of the startup algorithms. In particular, the verification of different startup algorithms used in three time-triggered architectures, TTA, FlexRay and TTCAN, are studied, compared and contrasted. Besides presenting the various verification approaches for these algorithms, the gaps and possible improvements on the verification efforts are also indicated.
In this work we propose techniques for efficient reachability analysis of the state space (e.g., ... more In this work we propose techniques for efficient reachability analysis of the state space (e.g., detection of bad states) using a combination of partial order and symmetry based reductions in a distributed setting. The proposed techniques are focused towards explicit state space enumeration based model-checkers like SPIN. We consider variants for both depth-first as well as breadth-first based generation of the reduced state graphs on-the-fly.
Short text is a popular avenue of sharing feedback, opinions and reviews on social media, e-comme... more Short text is a popular avenue of sharing feedback, opinions and reviews on social media, e-commerce platforms, etc. Many companies need to extract meaningful information (which may include thematic content as well as semantic polarity) out of such short texts to understand users’ behaviour. However, obtaining high quality sentiment-associated and human interpretable themes still remains a challenge for short texts. In this paper we develop ELJST, an embedding enhanced generative joint sentiment-topic model that can discover more coherent and diverse topics from short texts. It uses Markov Random Field Regularizer that can be seen as generalisation of skip-gram based models. Further, it can leverage higher order semantic information appearing in word embedding, such as self-attention weights in graphical models. Our results show an average improvement of 10% in topic coherence and 5% in topic diversification over baselines. Finally, ELJST helps understand users’ behaviour at more gr...
Business process models expressed in languages such as BPMN (Business Process Model and Notation)... more Business process models expressed in languages such as BPMN (Business Process Model and Notation), play a critical role in implementing the workflows in modern enterprises. However, control flow errors such as deadlocks and lack of synchronization, and syntactic errors arising out of poor modeling practices often occur in industrial process models. A major challenge is to provide the means and methods to detect such errors and more importantly, to identify the location of each error. In this work, we develop a formal framework of diagnosing errors by locating their occurrence nodes in business process models at the level of sub-processes and swim-lanes. We use graph-theoretic techniques and Petri net-based analyses to detect syntactic and control flow-related errors respectively. While syntactic errors can be easily located on the processes themselves, we project control-related errors on processes using a mapping from Petri nets to processes. We use this framework to analyze a samp...
Ticketing system is an example of a Service System (SS) which is responsible for handling huge vo... more Ticketing system is an example of a Service System (SS) which is responsible for handling huge volumes of tickets generated by large enterprise IT (Information Technology) infrastructure components, and ensuring smooth operation. The system maintains the provision of recording the time that reflects when a ticket is opened, acknowledged to user, resolved and/or closed, from which different QoS parameters could be obtained. For example, Resolution Time can be computed as the difference of resolution date and opening date of the ticket. One needs to use new technology solutions in QoS-related analysis like categorization of tickets according to their QoS, predicting QoS parameters for new tickets etc., to improve the performance of the SS. In this work we propose boosting oriented solutions to QoS prediction of tickets using crisp and fuzzy set models of QoS. In particular, we employ a two-stage analysis framework for QoS prediction for incoming tickets which includes clustering incid...
We revisit the problem of real-time verication with dense time dynamics using timeout and calenda... more We revisit the problem of real-time verication with dense time dynamics using timeout and calendar based models, originally proposed by Dutertre and Sorea, and simplify this to a nite state verication problem. To overcome the complexity of verication of real-time systems with dense time dynamics, Dutertre and Sorea, proposed timeout and calender based transition systems to model the behavior of real-time systems and veried safety properties using k-induction in association with bounded model checking. In this work, we introduce a specication formalism for these models in terms of Timed Transition Diagrams and capture their behavior in terms of semantics of Timed Transition Systems. Further, we discuss a technique, which reduces the problem of verication of qualitative temporal properties on innite state space of (a large fragment of) these timeout and calender based transition systems into that on clockless nite state models through a two-step process comprising of digitization and ...
A semantic annotation of business processes with concepts from ontology has become necessity in s... more A semantic annotation of business processes with concepts from ontology has become necessity in service provisioning. There have been few work on semantically labeling business processes in terms of ontology that formalizes business process structure, business domains etc. However, dynamic behavior of a process cannot be captured by such means as ontology languages are not suitable for specifying behavioral semantics. In this work, we propose a method for labeling and specifying business processes by using hybrid programs as the knowledge representation formalism. The formalism of hybrid programs integrates normal programs (using the parlance of logic programming) with ontology specified in OWL-DL (semantic web standard).
Several methods on simultaneous detection of sentiment and topics have been proposed to obtain su... more Several methods on simultaneous detection of sentiment and topics have been proposed to obtain subjective information such as opinion, attitude and feelings expressed in texts. Most of the techniques fail to produce desired results for short texts. In this paper, we propose LJST, a labeled joint sentiment-topic model particularly for short texts. It uses a probabilistic framework based on latent Dirichlet allocation. LJST is semi-supervised-it predicts the sentiment values for unlabeled texts in presence of a partially labeled texts with sentiment values. To address the sparsity problem in short text, we modify LJST and introduce Bi-LJST, which uses bi-terms (all possible pairs of words in a document) in place of unigrams for learning the topics by directly generating word co-occurrence patterns in each text and expressing the topics in terms of these patterns. Specifically, we have proposed a semi-supervised approach of extracting joint sentiment-topic model for short texts by incorporating bi-terms. Extensive experiments on three real-world datasets show that our methods perform consistently better than three other baselines in terms of document-level and topic-level sentiment prediction, and topic discovery-LJST using bi-term models outperforms the best baseline by producing 12% lower RMSE for document-level sentiment prediction and 6% higher F1 score for topic-sentiment prediction.
Process modeling forms a core activity in many organizations in which different entities and stak... more Process modeling forms a core activity in many organizations in which different entities and stakeholders interact for smooth operation and management of enterprises. There have been few work on semantically labeling business processes using OWL-DL that formalize business process structure and query them. However, all these methods suffer from few limitations such as lack of a modular approach of ontology design, no guarantee of a consistent ontology development with TBox and ABox axioms and no provision of combining control flow relations of the main process and its sub-processes. In this work, we propose an approach for labeling and specifying business processes by using hybrid programs which offers modular ontology design, consistent ontology design of each module and unified control flow for process and its sub-processes. This formalism of hybrid programs integrates ontology specified in OWL-DL with SWRL (Semantic Web Rules Language) rules. Further we report on our experimental effort on modeling industrial business processes with this hybrid formalism. We also present a case study of an industrial business process to illustrate our modeling approach which can aid in business knowledge management.
The goal of a Service System in an organization is to deliver uninterrupted service towards achie... more The goal of a Service System in an organization is to deliver uninterrupted service towards achieving business success. Ticketing system is an example of a Service System which is responsible for handling huge volumes of tickets generated by large enterprise IT (Information Technology) infrastructure components and ensuring smooth operation. Instead of manual screening one needs to extract information automatically from them to gain insights to improve operational efficiency. To ensure better operation we propose a framework to cluster incident tickets based on their textual context that can eliminate manual classification of them, which is labor intensive and costly. Further we label each of the clusters by generating meaningful keywords as logical itemsets, extracting candidate labels from Wikipedia articles, and finally scoring each of labels against each cluster. These labels can reflect an adequate and concise specification of each cluster. Further we experiment our approach with industrial ticket data from three different domains and report on the learned experience. We believe that our framework for clustering and labeling will enable enterprises to prioritize the issues in their IT infrastructure and improve the reliability and availability of their services.
2016 IEEE International Conference on Services Computing (SCC), 2016
These days IT service providers are rapidly embracing an automated services delivery model in ord... more These days IT service providers are rapidly embracing an automated services delivery model in order to keep pace with advances in technology and demanding market pressure to reduce and maintain quality. Application development and maintenance is a good example of a service system in which a sizable volume of tickets are raised everyday for different issues to get resolved with a view to deliver uninterrupted service. An issue is captured as summary on the ticket and once a ticket is resolved, the solution is also noted down on the ticket as resolution. It will be beneficial to automatically extract information from the description of tickets to improve operations like identifying critical and frequent issues, grouping of tickets based on textual content, suggesting remedial measures for them etc. In particular, the maintenance people can save a lot of effort and time if they have access to past remedial actions for similar kind of tickets raised earlier based on history data. In this work we propose an automated method based on background knowledge of tickets for recovering resolutions for fresh tickets using unsupervised learning and the traditional kNN (k-nearest neighbor) search. In absence of domain ontology we use ticket description to extract ontology which is grounded in WordNet. The experiment of our dataset shows that we are able to achieve a promising similarity match of about 48% between the suggestions and the actual resolution which shows an improvement over clustering without background knowledge.
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Papers by Suman Roy