International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2024
The ColabCode is a groundbreaking solution that empowers geographically dispersed individuals wor... more The ColabCode is a groundbreaking solution that empowers geographically dispersed individuals working on the same project to collaborate seamlessly and simultaneously. Leveraging advanced technologies and an intuitive user interface, ColabCode provides a comprehensive platform where participants can collaborate, share code, and communicate effectively in real time.ColabCode addresses the challenges faced by distributed teams, allowing them to work cohesively on shared projects. By providing a unified workspace accessible from anywhere, participants can log in to the platform and instantly join the project in progress. Regardless of their location or time zone, team members can start working together, eliminating delays caused by coordination issues. The heart of ColabCode lies in its diverse programming language support. With built-in capabilities for various programming languages such as Python, Java, JavaScript, C++, and more, team members can seamlessly contribute code in their preferred language. This flexibility fosters inclusivity and encourages diverse skill sets, ensuring each member can work efficiently using their expertise.
INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2023
Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity du... more Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity due to its usefulness in meeting customers' needs by helping them find things they might like based on past purchases and interests. Despite their great effectiveness in generating recommendations, conventional RS techniques fall short when it comes to providing accurate ideas due to problems with concept drift. The development of temporal models to account for concept drifts and guarantee more accurate recommendations has been the focus of a lot of research in the wake of these issues, giving rise to dynamic recommender systems (DRSs). However, the bulk of the effort needed to address the drift of interest is put in developing long-term and short-term models for users. It is not possible to dynamically track users' changing interests. We express doubts in this position paper about the practice of computing evaluation metrics for recommender systems as single numbers since these values only represent average effectiveness over a very long time period (for example, a year or longer). This approach only provides a vague, unchanging picture of the facts. To better understand the performance of recommender systems, we propose that researchers compute metrics across time series such as weeks or months and present the results visually, using a line chart, for instance. Insightful forecasts about an algorithm's future performance can be made with the use of results that show how an algorithm's effectiveness evolves over time. As a result, we'll be able to make more informed selections about which algorithms to utilize in a recommender system by collecting more data on an algorithm's performance over time, spotting trends, and developing more accurate forecasts about an algorithm's future performance.
Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity du... more Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity due to its usefulness in meeting customers' needs by helping them find things they might like based on past purchases and interests. Despite their great effectiveness in generating recommendations, conventional RS techniques fall short when it comes to providing accurate ideas due to problems with concept drift. The development of temporal models to account for concept drifts and guarantee more accurate recommendations has been the focus of a lot of research in the wake of these issues, giving rise to dynamic recommender systems (DRSs). However, the bulk of the effort needed to address the drift of interest is put in developing long-term and short-term models for users. It is not possible to dynamically track users' changing interests. We express doubts in this position paper about the practice of computing evaluation metrics for recommender systems as single numbers since these values only represent average effectiveness over a very long time period (for example, a year or longer). This approach only provides a vague, unchanging picture of the facts. To better understand the performance of recommender systems, we propose that researchers compute metrics across time series such as weeks or months and present the results visually, using a line chart, for instance. Insightful forecasts about an algorithm's future performance can be made with the use of results that show how an algorithm's effectiveness evolves over time. As a result, we'll be able to make more informed selections about which algorithms to utilize in a recommender system by collecting more data on an algorithm's performance over time, spotting trends, and developing more accurate forecasts about an algorithm's future performance.
Cloud computing is the term which opens the new era of computing terminology or metaphor based ut... more Cloud computing is the term which opens the new era of computing terminology or metaphor based utility and consumption of computing resources over web. The internet and central remote services of cloud computing retains the data, applications which offers much more efficient computing by centralizing storage, memory, processing bandwidth and other concerned network based terminologies.DNS3 C PRO is cloud based new technique is making the user able to do C programming on mobile devices through which the user can do this work anytime (24 hours) and anywhere (either college or home) as well as to save the installation effort of software (like Turbo C) on PC.This can also save the memory storage of PC.
Entity resolution is the problem of identifying which records in database refer to the same entit... more Entity resolution is the problem of identifying which records in database refer to the same entity.Records linkage is the process of matching records between two or multiple dataset that represent same real world entity.Computing similarities between all pairs of records which can be very expensive for large datasets.Blocking techniques eliminates this problem. In practice, many applications need to resolve large data sets efficiently, but do not require the ER result to be exact. For example, people data from the Web may simply be too large to completely resolve with a reasonable amount of work. As another example, real-time applications may not be able to tolerate any ER processing that takes longer than a certain amount of time. This system investigates how we can maximize the progress of ER with a limited amount of work using “hints,” which give information on records that are likely to refer to the same real-world entity.
Cloud computing is the term which opens the new era of computing terminology or metaphor based ut... more Cloud computing is the term which opens the new era of computing terminology or metaphor based utility and consumption of computing resources over web. The internet and central remote services of cloud computing retains the data, applications which offers much more efficient computing by centralizing storage, memory, processing bandwidth and other concerned network based terminologies.DNS3 C PRO is cloud based new technique is making the user able to do C programming on mobile devices through which the user can do this work anytime (24 hours) and anywhere (either college or home) as well as to save the installation effort of software (like Turbo C) on PC .This can also save the memory storage of PC.
International Journal of Computer Applications, 2015
Cloud computing is the term which opens the new era of computing terminology or metaphor based ut... more Cloud computing is the term which opens the new era of computing terminology or metaphor based utility and consumption of computing resources over web. The internet and central remote services of cloud computing retains the data, applications which offers much more efficient computing by centralizing storage, memory, processing bandwidth and other concerned network based terminologies.DNS3 C PRO is cloud based new technique is making the user able to do C programming on mobile devices through which the user can do this work anytime (24 hours) and anywhere (either college or home) as well as to save the installation effort of software (like Turbo C) on PC .This can also save the memory storage of PC.
International Journal of Computer Applications, 2015
In order to update k-anonymous and confidential database, the suppression based and generalizatio... more In order to update k-anonymous and confidential database, the suppression based and generalization based updating protocol technique has been proposed. These protocols check whether the database inserted with the new tuple is still k-anonymous without knowing the content of the table and database respectively. But these methods will not work if initial database is empty. Also, if the incoming tuple that fails the test of these updating protocols, there is no solution for which action to be taken. So, in this paper we propose two solutions based on pending tuple set (i.e. a collection of all tuples that fails anonymous property of database) namely the private extraction of k-anonymous part of pending tuple set or kanonymization of pending tuple set by privately suppressing entries.
International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2024
The ColabCode is a groundbreaking solution that empowers geographically dispersed individuals wor... more The ColabCode is a groundbreaking solution that empowers geographically dispersed individuals working on the same project to collaborate seamlessly and simultaneously. Leveraging advanced technologies and an intuitive user interface, ColabCode provides a comprehensive platform where participants can collaborate, share code, and communicate effectively in real time.ColabCode addresses the challenges faced by distributed teams, allowing them to work cohesively on shared projects. By providing a unified workspace accessible from anywhere, participants can log in to the platform and instantly join the project in progress. Regardless of their location or time zone, team members can start working together, eliminating delays caused by coordination issues. The heart of ColabCode lies in its diverse programming language support. With built-in capabilities for various programming languages such as Python, Java, JavaScript, C++, and more, team members can seamlessly contribute code in their preferred language. This flexibility fosters inclusivity and encourages diverse skill sets, ensuring each member can work efficiently using their expertise.
INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING, 2023
Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity du... more Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity due to its usefulness in meeting customers' needs by helping them find things they might like based on past purchases and interests. Despite their great effectiveness in generating recommendations, conventional RS techniques fall short when it comes to providing accurate ideas due to problems with concept drift. The development of temporal models to account for concept drifts and guarantee more accurate recommendations has been the focus of a lot of research in the wake of these issues, giving rise to dynamic recommender systems (DRSs). However, the bulk of the effort needed to address the drift of interest is put in developing long-term and short-term models for users. It is not possible to dynamically track users' changing interests. We express doubts in this position paper about the practice of computing evaluation metrics for recommender systems as single numbers since these values only represent average effectiveness over a very long time period (for example, a year or longer). This approach only provides a vague, unchanging picture of the facts. To better understand the performance of recommender systems, we propose that researchers compute metrics across time series such as weeks or months and present the results visually, using a line chart, for instance. Insightful forecasts about an algorithm's future performance can be made with the use of results that show how an algorithm's effectiveness evolves over time. As a result, we'll be able to make more informed selections about which algorithms to utilize in a recommender system by collecting more data on an algorithm's performance over time, spotting trends, and developing more accurate forecasts about an algorithm's future performance.
Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity du... more Despite challenges like concept drifts, or temporal dynamics in RS, RS has grown in popularity due to its usefulness in meeting customers' needs by helping them find things they might like based on past purchases and interests. Despite their great effectiveness in generating recommendations, conventional RS techniques fall short when it comes to providing accurate ideas due to problems with concept drift. The development of temporal models to account for concept drifts and guarantee more accurate recommendations has been the focus of a lot of research in the wake of these issues, giving rise to dynamic recommender systems (DRSs). However, the bulk of the effort needed to address the drift of interest is put in developing long-term and short-term models for users. It is not possible to dynamically track users' changing interests. We express doubts in this position paper about the practice of computing evaluation metrics for recommender systems as single numbers since these values only represent average effectiveness over a very long time period (for example, a year or longer). This approach only provides a vague, unchanging picture of the facts. To better understand the performance of recommender systems, we propose that researchers compute metrics across time series such as weeks or months and present the results visually, using a line chart, for instance. Insightful forecasts about an algorithm's future performance can be made with the use of results that show how an algorithm's effectiveness evolves over time. As a result, we'll be able to make more informed selections about which algorithms to utilize in a recommender system by collecting more data on an algorithm's performance over time, spotting trends, and developing more accurate forecasts about an algorithm's future performance.
Cloud computing is the term which opens the new era of computing terminology or metaphor based ut... more Cloud computing is the term which opens the new era of computing terminology or metaphor based utility and consumption of computing resources over web. The internet and central remote services of cloud computing retains the data, applications which offers much more efficient computing by centralizing storage, memory, processing bandwidth and other concerned network based terminologies.DNS3 C PRO is cloud based new technique is making the user able to do C programming on mobile devices through which the user can do this work anytime (24 hours) and anywhere (either college or home) as well as to save the installation effort of software (like Turbo C) on PC.This can also save the memory storage of PC.
Entity resolution is the problem of identifying which records in database refer to the same entit... more Entity resolution is the problem of identifying which records in database refer to the same entity.Records linkage is the process of matching records between two or multiple dataset that represent same real world entity.Computing similarities between all pairs of records which can be very expensive for large datasets.Blocking techniques eliminates this problem. In practice, many applications need to resolve large data sets efficiently, but do not require the ER result to be exact. For example, people data from the Web may simply be too large to completely resolve with a reasonable amount of work. As another example, real-time applications may not be able to tolerate any ER processing that takes longer than a certain amount of time. This system investigates how we can maximize the progress of ER with a limited amount of work using “hints,” which give information on records that are likely to refer to the same real-world entity.
Cloud computing is the term which opens the new era of computing terminology or metaphor based ut... more Cloud computing is the term which opens the new era of computing terminology or metaphor based utility and consumption of computing resources over web. The internet and central remote services of cloud computing retains the data, applications which offers much more efficient computing by centralizing storage, memory, processing bandwidth and other concerned network based terminologies.DNS3 C PRO is cloud based new technique is making the user able to do C programming on mobile devices through which the user can do this work anytime (24 hours) and anywhere (either college or home) as well as to save the installation effort of software (like Turbo C) on PC .This can also save the memory storage of PC.
International Journal of Computer Applications, 2015
Cloud computing is the term which opens the new era of computing terminology or metaphor based ut... more Cloud computing is the term which opens the new era of computing terminology or metaphor based utility and consumption of computing resources over web. The internet and central remote services of cloud computing retains the data, applications which offers much more efficient computing by centralizing storage, memory, processing bandwidth and other concerned network based terminologies.DNS3 C PRO is cloud based new technique is making the user able to do C programming on mobile devices through which the user can do this work anytime (24 hours) and anywhere (either college or home) as well as to save the installation effort of software (like Turbo C) on PC .This can also save the memory storage of PC.
International Journal of Computer Applications, 2015
In order to update k-anonymous and confidential database, the suppression based and generalizatio... more In order to update k-anonymous and confidential database, the suppression based and generalization based updating protocol technique has been proposed. These protocols check whether the database inserted with the new tuple is still k-anonymous without knowing the content of the table and database respectively. But these methods will not work if initial database is empty. Also, if the incoming tuple that fails the test of these updating protocols, there is no solution for which action to be taken. So, in this paper we propose two solutions based on pending tuple set (i.e. a collection of all tuples that fails anonymous property of database) namely the private extraction of k-anonymous part of pending tuple set or kanonymization of pending tuple set by privately suppressing entries.
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Papers by Vinod Ingale