Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995792
M. Mohd, Nazlena Mohamad Ali
This paper describes our overview on crime news retrieval system for Malaysian context. We discuss a framework of an Interactive Malaysia Crime News Retrieval System (i-JEN) from the perspective of technical possibilities. Our main objectives are to construct crime based event; investigate the use of crime based event in improving the classification and clustering; develop an interactive crime news retrieval system; visualize crime news in an effective and interactive way; and to evaluate the usability and system performance. The work has an aim to organize, retrieve and present the crime news interactively and in a most effective way. Our main target users in this work are the public users, news analyst and policeman. We also integrated the data we get from the Bernama news agency in the design and development of the system.
{"title":"An Interactive Malaysia Crime News Retrieval System","authors":"M. Mohd, Nazlena Mohamad Ali","doi":"10.1109/STAIR.2011.5995792","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995792","url":null,"abstract":"This paper describes our overview on crime news retrieval system for Malaysian context. We discuss a framework of an Interactive Malaysia Crime News Retrieval System (i-JEN) from the perspective of technical possibilities. Our main objectives are to construct crime based event; investigate the use of crime based event in improving the classification and clustering; develop an interactive crime news retrieval system; visualize crime news in an effective and interactive way; and to evaluate the usability and system performance. The work has an aim to organize, retrieve and present the crime news interactively and in a most effective way. Our main target users in this work are the public users, news analyst and policeman. We also integrated the data we get from the Bernama news agency in the design and development of the system.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"339 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132196633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995758
M. Ismail, R. G. Raj, S. A. Kareem
Academic research almost without exception involves literature searches. The huge wealth of literature can be sorted using ontologies and eventually an ontologically based system may be able to extract relevant literature for researchers based on some simple queues such as research title or hypothesis. In this paper we introduce an ontology-based digital library system and detail the first component of the system that allows real time flexible ontology management. The flexibility aspect includes the modification of the ontology at any time, as well as full real time graphical representation and editing. We introduce our novel semi-formal representation scheme for ontologies that promotes ontology modifiability and adaptability.
{"title":"Dynamic ontology editor for a knowledge management system of scholarly activities","authors":"M. Ismail, R. G. Raj, S. A. Kareem","doi":"10.1109/STAIR.2011.5995758","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995758","url":null,"abstract":"Academic research almost without exception involves literature searches. The huge wealth of literature can be sorted using ontologies and eventually an ontologically based system may be able to extract relevant literature for researchers based on some simple queues such as research title or hypothesis. In this paper we introduce an ontology-based digital library system and detail the first component of the system that allows real time flexible ontology management. The flexibility aspect includes the modification of the ontology at any time, as well as full real time graphical representation and editing. We introduce our novel semi-formal representation scheme for ontologies that promotes ontology modifiability and adaptability.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122531228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995784
M. Mohd, F. Crestani, I. Ruthven
This paper discussed the construction of topics to be tracked and clusters to be detected in Topic Detection and Tracking (TDT) tasks. Single Pass Clustering was used to cluster the news articles. As a result, the TDT tasks contained a combination of a good and poor clustering performance based on the F1-measure. Therefore, the selection of clusters and topics from the clustering experiment is important in the Tracking and the Detection tasks. It has contributed towards the user experimental design.
{"title":"Construction of topics and clusters in Topic Detection and Tracking tasks","authors":"M. Mohd, F. Crestani, I. Ruthven","doi":"10.1109/STAIR.2011.5995784","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995784","url":null,"abstract":"This paper discussed the construction of topics to be tracked and clusters to be detected in Topic Detection and Tracking (TDT) tasks. Single Pass Clustering was used to cluster the news articles. As a result, the TDT tasks contained a combination of a good and poor clustering performance based on the F1-measure. Therefore, the selection of clusters and topics from the clustering experiment is important in the Tracking and the Detection tasks. It has contributed towards the user experimental design.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114809559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995806
A. Omar, Nazlena Mohamad Ali
This paper describes the work in measuring flow while interacting with multi-platform games interfaces. We identified different gaming platforms which are mobile and non-mobile platform. The objective of the study is to identify and measure the variation of flow in different platforms. The early pilot data are collected through a survey form that are designed based on GameFlow criteria. The GameFlow criteria consist of eight elements which are: concentration; challenge; skills; control; clear goals; feedback; immersion and social interaction. In this exploratory study, the questionnaires of the survey are slightly altered from the GameFlow criteria identified in the previous work. From the early survey data collected, it shows the variation of player's expression and thought towards different kind of gaming platforms. Finding also shows that PC and Console are preferred by the respondent as their main platform to play games. The finding of this exploratory study can be used as additional guidelines in the future development of games application.
{"title":"Measuring flow in gaming platforms","authors":"A. Omar, Nazlena Mohamad Ali","doi":"10.1109/STAIR.2011.5995806","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995806","url":null,"abstract":"This paper describes the work in measuring flow while interacting with multi-platform games interfaces. We identified different gaming platforms which are mobile and non-mobile platform. The objective of the study is to identify and measure the variation of flow in different platforms. The early pilot data are collected through a survey form that are designed based on GameFlow criteria. The GameFlow criteria consist of eight elements which are: concentration; challenge; skills; control; clear goals; feedback; immersion and social interaction. In this exploratory study, the questionnaires of the survey are slightly altered from the GameFlow criteria identified in the previous work. From the early survey data collected, it shows the variation of player's expression and thought towards different kind of gaming platforms. Finding also shows that PC and Console are preferred by the respondent as their main platform to play games. The finding of this exploratory study can be used as additional guidelines in the future development of games application.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114453766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995777
S. Saad, N. Salim, Suhaila Zainuddin
In this paper, we present our early stage on developing Ontology for Quranic translation English Text using ontology learning techniques. For this stage, we are focusing on the Solat subject. We explain the requirement to create the ontology based on understanding of the Quranic translation text. At the same time we discuss the creation of gold standard in order to evaluate the finding pattern based on ontology learning techniques.
{"title":"An early stage of knowledge acquisition based on Quranic text","authors":"S. Saad, N. Salim, Suhaila Zainuddin","doi":"10.1109/STAIR.2011.5995777","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995777","url":null,"abstract":"In this paper, we present our early stage on developing Ontology for Quranic translation English Text using ontology learning techniques. For this stage, we are focusing on the Solat subject. We explain the requirement to create the ontology based on understanding of the Quranic translation text. At the same time we discuss the creation of gold standard in order to evaluate the finding pattern based on ontology learning techniques.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128148692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995775
N. Jamil, A. Alhadi, S. Noah
Friendster, Facebook, Twitter and many other microblogs have been introduced since 2004. These web 2.0 applications have become a powerful tool for communication. Each social web site has millions of users whose interact with each other regardless of their location and distance. Therefore, the mechanism of recommendation system for these sites is important for users to find suitable friends. Name recommendation should be made based on the concept of homophily which stated that relationships between individuals who have in common is higher than individuals who have nothing in common. Twitter is one of the popular social web sites that were developed in 2006. Many of the Twitter users are passive users. They just follow other users but on the other side they do not have many followers. This problem arises because reciprocal relationship is not required in Twitter. To overcome this problem, a recommendation system can help users in searching friends by taking into account reciprocal relationships. The main goal of this study is to use collaborative filtering techniques to recommend names based on geographical location. User's location is taken from the user's profile by using coordinates of latitude and longitude. Celebrities profile data sets provided by the Korea Advanced Institute of Science and Technology (KAIST) are taken for testing purposes. The result of the testing indicates the potential of exploiting geographical locations in collaboratively recommending names within Twitter environment.
{"title":"A collaborative names recommendation in the Twitter environment based on location","authors":"N. Jamil, A. Alhadi, S. Noah","doi":"10.1109/STAIR.2011.5995775","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995775","url":null,"abstract":"Friendster, Facebook, Twitter and many other microblogs have been introduced since 2004. These web 2.0 applications have become a powerful tool for communication. Each social web site has millions of users whose interact with each other regardless of their location and distance. Therefore, the mechanism of recommendation system for these sites is important for users to find suitable friends. Name recommendation should be made based on the concept of homophily which stated that relationships between individuals who have in common is higher than individuals who have nothing in common. Twitter is one of the popular social web sites that were developed in 2006. Many of the Twitter users are passive users. They just follow other users but on the other side they do not have many followers. This problem arises because reciprocal relationship is not required in Twitter. To overcome this problem, a recommendation system can help users in searching friends by taking into account reciprocal relationships. The main goal of this study is to use collaborative filtering techniques to recommend names based on geographical location. User's location is taken from the user's profile by using coordinates of latitude and longitude. Celebrities profile data sets provided by the Korea Advanced Institute of Science and Technology (KAIST) are taken for testing purposes. The result of the testing indicates the potential of exploiting geographical locations in collaboratively recommending names within Twitter environment.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128782143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995787
Saravadee Sae Tan, E. Tang, Bali Ranaivo-Malançon, G. Sodhy
On the web, most structured document collections consist of documents from different sources and marked up with different types of structures. The diversity of structures has led to the emergence of heterogeneous structured documents. The heterogeneity of structured documents is one of the reason for query-document mismatch in structured document retrieval. In structured document retrieval, a user is assumed to have intimate knowledge of the document structures and is able to specify contextual constraints in their queries. However, it is impossible for the user to know all structures in heterogeneous structured document collections. In this paper, we propose to include similar correspondence relations in the representation model for structured document retrieval. The similar correspondences make the relations between similar contents explicit in order to improve structured document retrieval effectiveness. We introduce a generic and flexible structured document model to represent heterogeneous structured documents as well as the similar correspondences in the document collections. We also illustrate how the proposed model can be utilized in structured document retrieval.
{"title":"Modeling semantic correspondence in heterogeneous structured document collection","authors":"Saravadee Sae Tan, E. Tang, Bali Ranaivo-Malançon, G. Sodhy","doi":"10.1109/STAIR.2011.5995787","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995787","url":null,"abstract":"On the web, most structured document collections consist of documents from different sources and marked up with different types of structures. The diversity of structures has led to the emergence of heterogeneous structured documents. The heterogeneity of structured documents is one of the reason for query-document mismatch in structured document retrieval. In structured document retrieval, a user is assumed to have intimate knowledge of the document structures and is able to specify contextual constraints in their queries. However, it is impossible for the user to know all structures in heterogeneous structured document collections. In this paper, we propose to include similar correspondence relations in the representation model for structured document retrieval. The similar correspondences make the relations between similar contents explicit in order to improve structured document retrieval effectiveness. We introduce a generic and flexible structured document model to represent heterogeneous structured documents as well as the similar correspondences in the document collections. We also illustrate how the proposed model can be utilized in structured document retrieval.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"161 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125946652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995766
M. K. Nasution, S. Noah
There has been quite a number of research efforts in extracting academic social network from on-line open sources such as the DBLP, ACM DL and IEEXplore. Extraction of such a network is usually based on the concept of co-occurrences. One of the issues in such efforts is actually involved extracting reliable and trusted network particularly when dealing with the heterogeneity of features in the Web. In this paper we demonstrate the use of association rule to enhance existing superficial method for extracting social network from online database such as the DBLP. The approach proposed has shown the capacity to extract social relation as well as the strength of these relations.
{"title":"Extraction of academic social network from online database","authors":"M. K. Nasution, S. Noah","doi":"10.1109/STAIR.2011.5995766","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995766","url":null,"abstract":"There has been quite a number of research efforts in extracting academic social network from on-line open sources such as the DBLP, ACM DL and IEEXplore. Extraction of such a network is usually based on the concept of co-occurrences. One of the issues in such efforts is actually involved extracting reliable and trusted network particularly when dealing with the heterogeneity of features in the Web. In this paper we demonstrate the use of association rule to enhance existing superficial method for extracting social network from online database such as the DBLP. The approach proposed has shown the capacity to extract social relation as well as the strength of these relations.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125035755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995769
Kartinah Zen, D. A. Iskandar, Ongkir Linang
Traditionally, computer programming assignments are graded manually by educators. As this task is tedious, time-consuming and prone to bias, the need for automated grading tool is necessary to reduce the educators' burden and avoid inconsistency and favoritism. Recent researches have claimed that Latent Semantic Analysis (LSA) has the ability to represent human cognitive knowledge to assess essays, retrieving information, classification of documents and indexing. In this paper, we adapt LSA technique to grade computer programming assignments and observe how far it can be applied as an alternative approach to traditional grading methods by human. The grades of the assignments are generated from the cosine similarity that shows how close students' assignments to the model answers in the latent semantic vector space. The results show that LSA is not able to detect orders of computer programming and symbols; however, LSA is able to grade assignments faster and consistently, which avoid bias and reduces the time spent by human.
{"title":"Using Latent Semantic Analysis for automated grading programming assignments","authors":"Kartinah Zen, D. A. Iskandar, Ongkir Linang","doi":"10.1109/STAIR.2011.5995769","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995769","url":null,"abstract":"Traditionally, computer programming assignments are graded manually by educators. As this task is tedious, time-consuming and prone to bias, the need for automated grading tool is necessary to reduce the educators' burden and avoid inconsistency and favoritism. Recent researches have claimed that Latent Semantic Analysis (LSA) has the ability to represent human cognitive knowledge to assess essays, retrieving information, classification of documents and indexing. In this paper, we adapt LSA technique to grade computer programming assignments and observe how far it can be applied as an alternative approach to traditional grading methods by human. The grades of the assignments are generated from the cosine similarity that shows how close students' assignments to the model answers in the latent semantic vector space. The results show that LSA is not able to detect orders of computer programming and symbols; however, LSA is able to grade assignments faster and consistently, which avoid bias and reduces the time spent by human.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133278165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-06-28DOI: 10.1109/STAIR.2011.5995779
Yanti Idaya Aspura Mohd Khalid, S. Noah
Knowledge sharing communities like Wikipedia and automated extraction like DBpedia enable a large construction of machine processing knowledge bases with relational fact of entities. These options give a great opportunity for researcher to use it as a domain concept between low-level features and high-level concepts for image retrieval. The collection of images attached to entities, such as on-line news articles with images, are abundant on the Internet. Still, it is difficult to retrieve accurate information on these entities. Using entity names in a search engine yields large lists, but often results in imprecise and unsatisfactory outcomes. Our goal is to populate a knowledge base with on-line image news resources in the BBC sport domain. This system will yield high precision, a high recall and include diverse sports photos for specific entities. A multi-modality ontology retrieval system, with relational facts about entities for generating expanded queries, will be used to retrieve results. DBpedia will be used as a domain sport ontology description, and will be integrated with a textual description and a visual description, both generated by hand. To overcome semantic interoperability between ontologies, automated ontology alignment is used. In addition, visual similarity measures based on MPEG7 descriptions and SIFT features, are used for higher diversity in the final rankings.
{"title":"A framework for integrating DBpedia in a multi-modality ontology news image retrieval system","authors":"Yanti Idaya Aspura Mohd Khalid, S. Noah","doi":"10.1109/STAIR.2011.5995779","DOIUrl":"https://doi.org/10.1109/STAIR.2011.5995779","url":null,"abstract":"Knowledge sharing communities like Wikipedia and automated extraction like DBpedia enable a large construction of machine processing knowledge bases with relational fact of entities. These options give a great opportunity for researcher to use it as a domain concept between low-level features and high-level concepts for image retrieval. The collection of images attached to entities, such as on-line news articles with images, are abundant on the Internet. Still, it is difficult to retrieve accurate information on these entities. Using entity names in a search engine yields large lists, but often results in imprecise and unsatisfactory outcomes. Our goal is to populate a knowledge base with on-line image news resources in the BBC sport domain. This system will yield high precision, a high recall and include diverse sports photos for specific entities. A multi-modality ontology retrieval system, with relational facts about entities for generating expanded queries, will be used to retrieve results. DBpedia will be used as a domain sport ontology description, and will be integrated with a textual description and a visual description, both generated by hand. To overcome semantic interoperability between ontologies, automated ontology alignment is used. In addition, visual similarity measures based on MPEG7 descriptions and SIFT features, are used for higher diversity in the final rankings.","PeriodicalId":376671,"journal":{"name":"2011 International Conference on Semantic Technology and Information Retrieval","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116890692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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