J. Brank, Natasa Milic-Frayling, A. Frayling, G. Smyth
Routine user activities on the Web result in the revisitation of Web sites and pages. Standard browser applications provide limited support for this type of habitual behaviour. They typically expose lists of visited URLs that are automatically recorded by the system or manually created by the user, such as bookmarks. Studies have shown that these approaches are not successful in supporting routine user activities. Informed by our user research, we designed a browser feature that automatically exposes candidate URLs for revisitation by the user. In this paper, we describe and evaluate the algorithms that we use to model the user's habitual behaviour. We demonstrate how a structured navigation history model facilitates the discovery of relevant usage patterns and supports predictive algorithms that are applicable to relatively short personal navigation histories.
{"title":"Predictive algorithms for browser support of habitual user activities on the Web","authors":"J. Brank, Natasa Milic-Frayling, A. Frayling, G. Smyth","doi":"10.1109/WI.2005.116","DOIUrl":"https://doi.org/10.1109/WI.2005.116","url":null,"abstract":"Routine user activities on the Web result in the revisitation of Web sites and pages. Standard browser applications provide limited support for this type of habitual behaviour. They typically expose lists of visited URLs that are automatically recorded by the system or manually created by the user, such as bookmarks. Studies have shown that these approaches are not successful in supporting routine user activities. Informed by our user research, we designed a browser feature that automatically exposes candidate URLs for revisitation by the user. In this paper, we describe and evaluate the algorithms that we use to model the user's habitual behaviour. We demonstrate how a structured navigation history model facilitates the discovery of relevant usage patterns and supports predictive algorithms that are applicable to relatively short personal navigation histories.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121447662","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}
Recommender systems have gained successfully applications particular in e-commerce domain. However, existing recommendation approaches can not effectively deal with recommendation issue of one-and-only items occurred in government-to-business services, e.g. recommendation of trade exhibitions. Thus, in this study, we propose a novel approach by integrating semantic information with the traditional item-based collaborative filtering, and attempt to help the businesses choose the right trade exhibitions at the right time. The outcome of this study have tremendous significance in overcoming the 'new item' problem of existing recommendation approaches.
{"title":"Recommending trade exhibitions by integrating semantic information with collaborative filtering","authors":"Xuetao Guo, Jie Lu","doi":"10.1109/WI.2005.126","DOIUrl":"https://doi.org/10.1109/WI.2005.126","url":null,"abstract":"Recommender systems have gained successfully applications particular in e-commerce domain. However, existing recommendation approaches can not effectively deal with recommendation issue of one-and-only items occurred in government-to-business services, e.g. recommendation of trade exhibitions. Thus, in this study, we propose a novel approach by integrating semantic information with the traditional item-based collaborative filtering, and attempt to help the businesses choose the right trade exhibitions at the right time. The outcome of this study have tremendous significance in overcoming the 'new item' problem of existing recommendation approaches.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"248 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123107286","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}
A comparison method for Web pages in terms of visual similarity is proposed. Conventional Web information retrieval/gathering systems, such as search engines, extract keywords from HTML source files, based on which the similarity between pages is calculated. The extracted keywords are considered as semantic features representing the contents of Web pages. On the other hand, visual feature of Web pages is as important as semantic feature, because HTML is designed for visualizing a Web page in understandable manner for humans. The proposed method compares the layouts of Web pages based on image processing and graph matching. The experimental results show that the accuracy of layout analysis is 91.6% in average, and the visual similarity calculated by the proposed method is closer to the visual judgment by test subjects than color-based comparison method.
{"title":"Visual similarity comparison for Web page retrieval","authors":"Y. Takama, Noriaki Mitsuhashi","doi":"10.1109/WI.2005.157","DOIUrl":"https://doi.org/10.1109/WI.2005.157","url":null,"abstract":"A comparison method for Web pages in terms of visual similarity is proposed. Conventional Web information retrieval/gathering systems, such as search engines, extract keywords from HTML source files, based on which the similarity between pages is calculated. The extracted keywords are considered as semantic features representing the contents of Web pages. On the other hand, visual feature of Web pages is as important as semantic feature, because HTML is designed for visualizing a Web page in understandable manner for humans. The proposed method compares the layouts of Web pages based on image processing and graph matching. The experimental results show that the accuracy of layout analysis is 91.6% in average, and the visual similarity calculated by the proposed method is closer to the visual judgment by test subjects than color-based comparison method.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115500947","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}
Text classification usually assumed a word-based document representation. In this paper, we propose a new approach to integrate compound terms in Bayesian text classification. Compound terms are used as complementary features to single words. An acute problem is to consider their dependence with the component words. In this paper, we propose to use smoothing techniques to combine both compound term and word representations. Experiments have been conducted on two corpora. Our results show that this approach can slightly but steadily improve the classification performance on both test corpora.
{"title":"Integrating compound terms in Bayesian text classification","authors":"Jing Bai, Jian-Yun Nie, Guihong Cao","doi":"10.1109/WI.2005.79","DOIUrl":"https://doi.org/10.1109/WI.2005.79","url":null,"abstract":"Text classification usually assumed a word-based document representation. In this paper, we propose a new approach to integrate compound terms in Bayesian text classification. Compound terms are used as complementary features to single words. An acute problem is to consider their dependence with the component words. In this paper, we propose to use smoothing techniques to combine both compound term and word representations. Experiments have been conducted on two corpora. Our results show that this approach can slightly but steadily improve the classification performance on both test corpora.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132526019","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}
The use of recommender systems (RS) has become common in several e-commerce Web sites. Collaborative filtering is one of the most popular RS techniques. It infers a user's predilections based on similarity with other users. However, to work correctly, the RS depends on the evaluator's participation with truly opinions. The HYRIWYG mechanism proposes an incentive model to motivate users to contribute with a high number of opinions and, more important, guaranteeing the truthfulness of the information. In this paper, we present HYRIWYG mechanism and discuss it using an empirical study in the movie evaluation domain. Initial results highlight the great potential benefits of using this kind of incentive mechanism.
{"title":"Applying the HYRIWYG incentive mechanism in a recommender system","authors":"A. C. Garcia, L. Ciuffo","doi":"10.1109/WI.2005.33","DOIUrl":"https://doi.org/10.1109/WI.2005.33","url":null,"abstract":"The use of recommender systems (RS) has become common in several e-commerce Web sites. Collaborative filtering is one of the most popular RS techniques. It infers a user's predilections based on similarity with other users. However, to work correctly, the RS depends on the evaluator's participation with truly opinions. The HYRIWYG mechanism proposes an incentive model to motivate users to contribute with a high number of opinions and, more important, guaranteeing the truthfulness of the information. In this paper, we present HYRIWYG mechanism and discuss it using an empirical study in the movie evaluation domain. Initial results highlight the great potential benefits of using this kind of incentive mechanism.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132555750","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}
Given the large heterogeneity of the World Wide Web, using metadata on the search engines side seems to be a useful track for information retrieval. Though, because a manual qualification at the Web scale is not accessible, this track is little followed. We propose a semi-automatic method for propagating metadata. In a first step, homogeneous corpus are extracted. We used in our study the following properties: the authority type, the site type, the information type, and the page type. This first step is realized by a clusterization which uses a similarity measure based on the co-citation frequency between pages. Given the cluster hierarchy, the second step selects a reduced number of documents to be manually qualified and propagates the given metadata values to the other documents belonging to the same cluster. A qualitative evaluation and a preliminary study about the scalability of this method are presented.
{"title":"Metadata propagation in the Web using co-citations","authors":"Camille Prime-Claverie, M. Beigbeder, T. Lafouge","doi":"10.1109/WI.2005.95","DOIUrl":"https://doi.org/10.1109/WI.2005.95","url":null,"abstract":"Given the large heterogeneity of the World Wide Web, using metadata on the search engines side seems to be a useful track for information retrieval. Though, because a manual qualification at the Web scale is not accessible, this track is little followed. We propose a semi-automatic method for propagating metadata. In a first step, homogeneous corpus are extracted. We used in our study the following properties: the authority type, the site type, the information type, and the page type. This first step is realized by a clusterization which uses a similarity measure based on the co-citation frequency between pages. Given the cluster hierarchy, the second step selects a reduced number of documents to be manually qualified and propagates the given metadata values to the other documents belonging to the same cluster. A qualitative evaluation and a preliminary study about the scalability of this method are presented.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131406795","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}
It is widely agreed that the semantic Web will be build on RDF. Therefore the success of the semantic Web also depends on the availability of a scalable and reliable infrastructure for storing and accessing RDF data. A number of storage and retrieval systems have been developed recently, but despite the inherently distributed nature of the semantic Web most of these systems do not support distributed storage and retrieval of data. In this paper we report our experiences with implementing a distributed storage and query infrastructure on top of an existing RDF infrastructure. We present the system architecture and discuss performance issues based on a set of experiments with the infrastructure. We conclude with an identification of remaining performance bottlenecks and point to further improvements.
{"title":"Implementation and evaluation of a distributed RDF storage and retrieval system","authors":"Gergely Adamku, H. Stuckenschmidt","doi":"10.1109/WI.2005.73","DOIUrl":"https://doi.org/10.1109/WI.2005.73","url":null,"abstract":"It is widely agreed that the semantic Web will be build on RDF. Therefore the success of the semantic Web also depends on the availability of a scalable and reliable infrastructure for storing and accessing RDF data. A number of storage and retrieval systems have been developed recently, but despite the inherently distributed nature of the semantic Web most of these systems do not support distributed storage and retrieval of data. In this paper we report our experiences with implementing a distributed storage and query infrastructure on top of an existing RDF infrastructure. We present the system architecture and discuss performance issues based on a set of experiments with the infrastructure. We conclude with an identification of remaining performance bottlenecks and point to further improvements.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131705513","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}
Structured link vector model (SLVM) is a recently proposed document representation that takes into account both structural and semantic information for measuring XML document similarity. Its formulation includes an element similarity matrix for capturing the semantic similarity between XML elements - the structural components of XML documents. In this paper, instead of applying heuristics to define the similarity matrix, we proposed to learn the matrix using pair wise similar training data in an iterative manner. In addition, we extended SLVM to SLVM-LSI by incorporating term semantics into SLVM using latent semantic indexing, with the element similarity related properties of the original SLVM preserved. For performance evaluation, we applied SLVM-LSI to similarity-based clustering of two XML datasets and the proposed SLVM-LSI was found to significantly outperform the conventional vector space model and the edit-distance based methods. The similarity matrix, obtained as a byproduct via the learning, can provide higher level knowledge about the semantic relationship between the XML elements.
结构化链接向量模型(Structured link vector model, SLVM)是最近提出的一种文档表示，它考虑了用于度量XML文档相似性的结构和语义信息。其公式包括一个元素相似矩阵，用于捕获XML元素(XML文档的结构组件)之间的语义相似度。在本文中，我们提出了使用成对相似训练数据以迭代的方式学习矩阵，而不是使用启发式方法来定义相似矩阵。此外，我们通过使用潜在语义索引将术语语义整合到SLVM中，将SLVM扩展到SLVM- lsi，同时保留了原始SLVM的元素相似相关属性。为了进行性能评估，我们将SLVM-LSI应用于基于相似性的两个XML数据集聚类，发现所提出的SLVM-LSI明显优于传统的向量空间模型和基于编辑距离的方法。通过学习获得的副产品相似度矩阵可以提供关于XML元素之间语义关系的更高层次的知识。
{"title":"Integrating element and term semantics for similarity-based XML document clustering","authors":"Jianwu Yang, W. K. Cheung, Xiaoou Chen","doi":"10.1109/WI.2005.80","DOIUrl":"https://doi.org/10.1109/WI.2005.80","url":null,"abstract":"Structured link vector model (SLVM) is a recently proposed document representation that takes into account both structural and semantic information for measuring XML document similarity. Its formulation includes an element similarity matrix for capturing the semantic similarity between XML elements - the structural components of XML documents. In this paper, instead of applying heuristics to define the similarity matrix, we proposed to learn the matrix using pair wise similar training data in an iterative manner. In addition, we extended SLVM to SLVM-LSI by incorporating term semantics into SLVM using latent semantic indexing, with the element similarity related properties of the original SLVM preserved. For performance evaluation, we applied SLVM-LSI to similarity-based clustering of two XML datasets and the proposed SLVM-LSI was found to significantly outperform the conventional vector space model and the edit-distance based methods. The similarity matrix, obtained as a byproduct via the learning, can provide higher level knowledge about the semantic relationship between the XML elements.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126668568","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}
Testing and evaluation is an integral part of the learning process. Educators have often tried to device methods for design of test-ware. Intelligent design and compilation of test-ware is a very interesting problem with immense applications. This research aims at automating the process of intelligent design of test-ware by providing qualitative assessment of questions. In this attempt, we provide some synthetic parameters for the evaluation of question in its concept space. The parameters are tested in some real world scenarios and intuitive inferences are deduced predicting the performance of the parameters. It is observed that the difficulty of a question is often a function of the concepts it tests. Concept knowledge can be represented in the form of linked concepts in semantic nets, the links representing the relationships between the concepts. If this directed graph is known, complexity of a question can be computed by synthetic means.
{"title":"A study of problem difficulty evaluation for semantic network ontology based intelligent courseware sharing","authors":"J. Khan, M. Hardas, Yongbin Ma","doi":"10.1109/WI.2005.15","DOIUrl":"https://doi.org/10.1109/WI.2005.15","url":null,"abstract":"Testing and evaluation is an integral part of the learning process. Educators have often tried to device methods for design of test-ware. Intelligent design and compilation of test-ware is a very interesting problem with immense applications. This research aims at automating the process of intelligent design of test-ware by providing qualitative assessment of questions. In this attempt, we provide some synthetic parameters for the evaluation of question in its concept space. The parameters are tested in some real world scenarios and intuitive inferences are deduced predicting the performance of the parameters. It is observed that the difficulty of a question is often a function of the concepts it tests. Concept knowledge can be represented in the form of linked concepts in semantic nets, the links representing the relationships between the concepts. If this directed graph is known, complexity of a question can be computed by synthetic means.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124002181","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}
S. Willmott, Félix Oscar Fernández Peña, C. Mérida-Campos, Ion Constantinescu, J. Dale, David Cabanillas
The integration of semantic Web and Web services technologies promises to be one of the most promising new areas for development of intelligent Web applications. One challenging area where these technologies meet is in explicit definitions of meaning for the messages exchanged between Web services - in other words, semantic definitions of the meanings of data / commands exchanged in the execution of a Web services based application. While current approaches such as OWL-S tackle these elements in service groundings by mapping processes to function calls with specific arguments, agent communication languages could provide a potentially richer alternative. The work presented here shows how this could be done by mapping the existing agent communication language (FIPA-ACL, FIPA-SL and associated standards developed by the foundation for intelligent physical agents) into OWL based representations which may then be readily used in a Web services environment.
{"title":"Adapting agent communication languages for semantic Web service inter-communication","authors":"S. Willmott, Félix Oscar Fernández Peña, C. Mérida-Campos, Ion Constantinescu, J. Dale, David Cabanillas","doi":"10.1109/WI.2005.20","DOIUrl":"https://doi.org/10.1109/WI.2005.20","url":null,"abstract":"The integration of semantic Web and Web services technologies promises to be one of the most promising new areas for development of intelligent Web applications. One challenging area where these technologies meet is in explicit definitions of meaning for the messages exchanged between Web services - in other words, semantic definitions of the meanings of data / commands exchanged in the execution of a Web services based application. While current approaches such as OWL-S tackle these elements in service groundings by mapping processes to function calls with specific arguments, agent communication languages could provide a potentially richer alternative. The work presented here shows how this could be done by mapping the existing agent communication language (FIPA-ACL, FIPA-SL and associated standards developed by the foundation for intelligent physical agents) into OWL based representations which may then be readily used in a Web services environment.","PeriodicalId":213856,"journal":{"name":"The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122156260","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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