This paper describes the creation of intervals of clusters of supermarket customers based on the ... more This paper describes the creation of intervals of clusters of supermarket customers based on the modified Kohonen self-organizing maps. The supermarket customers from three different markets serviced by a Canadian national supermarket chain were clustered based on their spending and visit patterns. The resulting rough set based clustering captured the similarities and differences between the characteristics of the three regions.
IEEE/WIC/ACM International Conference on Web Intelligence (WI'04), 2004
... The use of the matrix will make it possible to setup an iterative and interactive clustering ... more ... The use of the matrix will make it possible to setup an iterative and interactive clustering activity. ... Based on detailed analysis the clusters could be labelled as: 1: Loyal big spenders 2: Loyal moderate spenders 3: Semi-loyal big spenders ...
E-business and sensitive Internet applications are growing very fast, so the needs to protect suc... more E-business and sensitive Internet applications are growing very fast, so the needs to protect such applications are increased. Encryption algorithms play a main role in security. This work introduces a new key generation technique that can be used for enhancing the design of block cipher encryption algorithms, especially for DES to increase its key space; to be applicable in sensitive applications. This is based on the use of biometric key using the voice of speakers, extracting important features as formants and pitch of the speakers because it is unique for each one; in addition it applies crossover operations of genetic algorithm on biometric key to permute it. Finally it combines between stream ciphering and block ciphering algorithms (encryption of the crossover- biometric key using the RC4). The output Key-Stream bytes from the RC4 is then introduced to the DES algorithm to obtain the target ciphertext. The paper introduces also the idea of generating multi biometric keys by u...
... Lingras [19] applied the unsupervised rough set clustering based on GAs for grouping web user... more ... Lingras [19] applied the unsupervised rough set clustering based on GAs for grouping web users of a first year university course. ... Lingras [19] illustrated the feasibility of rough set clustering for developing user profiles on the web. ...
... The approach is based on a web page classification method, which uses attribute-oriented indu... more ... The approach is based on a web page classification method, which uses attribute-oriented induction according to related domain knowledge shown by a concept hierarchy tree. 2.3. ... Thesetechniques were applied in the areas of learning recommendation systems ( [11] , [62 ...
This paper introduces an evaluation methodologies for the e-learners' behaviour that will be... more This paper introduces an evaluation methodologies for the e-learners' behaviour that will be a feedback to the decision makers in e-learning system. Learner's profile plays a crucial role in the evaluation process to improve the e-learning process performance. The work focuses on the clustering of the e-learners based on their behaviour into specific categories that represent the learner's profiles. The learners' classes named as regular, workers, casual, bad, and absent. The work may answer the question of how to return bad students to be regular ones. The work presented the use of different fuzzy clustering techniques as fuzzy c-means and kernelized fuzzy c-means to find the learners' categories and predict their profiles. The paper presents the main phases as data description, preparation, features selection, and the experiments design using different fuzzy clustering models. Analysis of the obtained results and comparison with the real world behavior of ...
Temporal Web usage mining involves application of data mining techniques on temporal Web usage da... more Temporal Web usage mining involves application of data mining techniques on temporal Web usage data to discover temporal patterns, which describe the temporal behavior of Web users. Clusters and associations in Web usage mining do not necessarily have crisp boundaries. We introduce the temporal Web usage mining of Web users on one educational Web site, using the adapted Kohonen SOM
Web usage mining involves application of data mining techniques to discover usage patterns from t... more Web usage mining involves application of data mining techniques to discover usage patterns from the web data. Clustering is one of the important functions in web usage mining. The likelihood of bad or incomplete web usage data is higher than the conventional applications. The clusters and associations in web usage mining do not necessarily have crisp boundaries. Researchers have studied the possibility of using fuzzy sets in web mining clustering applications. Recent attempts have adapted the K-means clustering algorithm as well as genetic algorithms based on rough sets to find interval sets of clusters. The genetic algorithms based clustering may not be able to handle large amounts of data. The K-means algorithm does not lend itself well to adaptive clustering. This paper proposes an adaptation of Kohonen self-organizing maps based on the properties of rough sets, to find the interval sets of clusters. Experiments are used to create interval set representations of clusters of web visitors on three educational web sites.
Internet and expert systems have offered new ways of sharing and distributing knowledge, but ther... more Internet and expert systems have offered new ways of sharing and distributing knowledge, but there is a lack of researches in the area of web-based expert systems. This paper introduces a development of a web-based expert system for the regulations of civil service in the Kingdom of Saudi Arabia named as RCSES. It is the first time to develop such system (application of civil service regulations) as well the development of it using web-based approach. The proposed system considers 17 regulations of the civil service system. The different phases of developing the RCSES system are presented, as knowledge acquiring and selection, ontology and knowledge representations using XML format. XML-Rule-based knowledge sources and the inference mechanisms were implemented using ASP.net technique. An interactive tool for entering the ontology and knowledge base, and the inferencing was built. It gives the ability to use, modify, update, and extend the existing knowledge base in an easy way. The knowledge was validated by experts in the domain of civil service regulations, and the proposed RCSES was tested, verified, and validated by different technical users and the developers' staff. The RCSES system is compared with other related web based expert systems, that comparison proved the goodness, usability, and high performance of RCSES.
This paper describes the creation of intervals of clusters of supermarket customers based on the ... more This paper describes the creation of intervals of clusters of supermarket customers based on the modified Kohonen self-organizing maps. The supermarket customers from three different markets serviced by a Canadian national supermarket chain were clustered based on their spending and visit patterns. The resulting rough set based clustering captured the similarities and differences between the characteristics of the three regions.
IEEE/WIC/ACM International Conference on Web Intelligence (WI'04), 2004
... The use of the matrix will make it possible to setup an iterative and interactive clustering ... more ... The use of the matrix will make it possible to setup an iterative and interactive clustering activity. ... Based on detailed analysis the clusters could be labelled as: 1: Loyal big spenders 2: Loyal moderate spenders 3: Semi-loyal big spenders ...
E-business and sensitive Internet applications are growing very fast, so the needs to protect suc... more E-business and sensitive Internet applications are growing very fast, so the needs to protect such applications are increased. Encryption algorithms play a main role in security. This work introduces a new key generation technique that can be used for enhancing the design of block cipher encryption algorithms, especially for DES to increase its key space; to be applicable in sensitive applications. This is based on the use of biometric key using the voice of speakers, extracting important features as formants and pitch of the speakers because it is unique for each one; in addition it applies crossover operations of genetic algorithm on biometric key to permute it. Finally it combines between stream ciphering and block ciphering algorithms (encryption of the crossover- biometric key using the RC4). The output Key-Stream bytes from the RC4 is then introduced to the DES algorithm to obtain the target ciphertext. The paper introduces also the idea of generating multi biometric keys by u...
... Lingras [19] applied the unsupervised rough set clustering based on GAs for grouping web user... more ... Lingras [19] applied the unsupervised rough set clustering based on GAs for grouping web users of a first year university course. ... Lingras [19] illustrated the feasibility of rough set clustering for developing user profiles on the web. ...
... The approach is based on a web page classification method, which uses attribute-oriented indu... more ... The approach is based on a web page classification method, which uses attribute-oriented induction according to related domain knowledge shown by a concept hierarchy tree. 2.3. ... Thesetechniques were applied in the areas of learning recommendation systems ( [11] , [62 ...
This paper introduces an evaluation methodologies for the e-learners' behaviour that will be... more This paper introduces an evaluation methodologies for the e-learners' behaviour that will be a feedback to the decision makers in e-learning system. Learner's profile plays a crucial role in the evaluation process to improve the e-learning process performance. The work focuses on the clustering of the e-learners based on their behaviour into specific categories that represent the learner's profiles. The learners' classes named as regular, workers, casual, bad, and absent. The work may answer the question of how to return bad students to be regular ones. The work presented the use of different fuzzy clustering techniques as fuzzy c-means and kernelized fuzzy c-means to find the learners' categories and predict their profiles. The paper presents the main phases as data description, preparation, features selection, and the experiments design using different fuzzy clustering models. Analysis of the obtained results and comparison with the real world behavior of ...
Temporal Web usage mining involves application of data mining techniques on temporal Web usage da... more Temporal Web usage mining involves application of data mining techniques on temporal Web usage data to discover temporal patterns, which describe the temporal behavior of Web users. Clusters and associations in Web usage mining do not necessarily have crisp boundaries. We introduce the temporal Web usage mining of Web users on one educational Web site, using the adapted Kohonen SOM
Web usage mining involves application of data mining techniques to discover usage patterns from t... more Web usage mining involves application of data mining techniques to discover usage patterns from the web data. Clustering is one of the important functions in web usage mining. The likelihood of bad or incomplete web usage data is higher than the conventional applications. The clusters and associations in web usage mining do not necessarily have crisp boundaries. Researchers have studied the possibility of using fuzzy sets in web mining clustering applications. Recent attempts have adapted the K-means clustering algorithm as well as genetic algorithms based on rough sets to find interval sets of clusters. The genetic algorithms based clustering may not be able to handle large amounts of data. The K-means algorithm does not lend itself well to adaptive clustering. This paper proposes an adaptation of Kohonen self-organizing maps based on the properties of rough sets, to find the interval sets of clusters. Experiments are used to create interval set representations of clusters of web visitors on three educational web sites.
Internet and expert systems have offered new ways of sharing and distributing knowledge, but ther... more Internet and expert systems have offered new ways of sharing and distributing knowledge, but there is a lack of researches in the area of web-based expert systems. This paper introduces a development of a web-based expert system for the regulations of civil service in the Kingdom of Saudi Arabia named as RCSES. It is the first time to develop such system (application of civil service regulations) as well the development of it using web-based approach. The proposed system considers 17 regulations of the civil service system. The different phases of developing the RCSES system are presented, as knowledge acquiring and selection, ontology and knowledge representations using XML format. XML-Rule-based knowledge sources and the inference mechanisms were implemented using ASP.net technique. An interactive tool for entering the ontology and knowledge base, and the inferencing was built. It gives the ability to use, modify, update, and extend the existing knowledge base in an easy way. The knowledge was validated by experts in the domain of civil service regulations, and the proposed RCSES was tested, verified, and validated by different technical users and the developers' staff. The RCSES system is compared with other related web based expert systems, that comparison proved the goodness, usability, and high performance of RCSES.
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Papers by Mofreh Hogo