It is becoming increasingly important to facilitate the integrated management of user information. Exchanging user information across heterogeneous systems has many benefits, particularly in enhancing the quality and quantity of user information available for personalization. One common approach to user model interoperability is the use of mapping tools to manually build rich executable mappings between user models. A key problem with existing approaches is that the mapping tools are often too generic for these specialized tasks and do not provide any support to an administrator mapping in a specific domain such as user models. This paper presents a novel approach to user model interoperability which lowers the complexity and provides support to administrators in completing user model mappings. The domain-aware approach to user model interoperability incorporates interchangeable domain knowledge directly into the integration tools. This approach was implemented in a system called FUMES which is a mapping creation and execution environment that includes two domain-aware mechanisms; a canonical user model and user model mapping types. FUMES was deployed in an integration of existing user models and the domain-aware approach was then evaluated in a user study. The evaluation consisted of a direct comparison with a generic approach to user model interoperability which was applied using the commercial mapping tool, Altova Mapforce. The results of this evaluation demonstrate improvements in mapping accuracy and usability when using the domain-aware approach compared to the generic mapping approach.
{"title":"Evaluation of a domain-aware approach to user model interoperability","authors":"Eddie Walsh, A. O'Connor, V. Wade","doi":"10.1145/2309996.2310030","DOIUrl":"https://doi.org/10.1145/2309996.2310030","url":null,"abstract":"It is becoming increasingly important to facilitate the integrated management of user information. Exchanging user information across heterogeneous systems has many benefits, particularly in enhancing the quality and quantity of user information available for personalization. One common approach to user model interoperability is the use of mapping tools to manually build rich executable mappings between user models. A key problem with existing approaches is that the mapping tools are often too generic for these specialized tasks and do not provide any support to an administrator mapping in a specific domain such as user models. This paper presents a novel approach to user model interoperability which lowers the complexity and provides support to administrators in completing user model mappings. The domain-aware approach to user model interoperability incorporates interchangeable domain knowledge directly into the integration tools. This approach was implemented in a system called FUMES which is a mapping creation and execution environment that includes two domain-aware mechanisms; a canonical user model and user model mapping types. FUMES was deployed in an integration of existing user models and the domain-aware approach was then evaluated in a user study. The evaluation consisted of a direct comparison with a generic approach to user model interoperability which was applied using the commercial mapping tool, Altova Mapforce. The results of this evaluation demonstrate improvements in mapping accuracy and usability when using the domain-aware approach compared to the generic mapping approach.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"115 1","pages":"197-206"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90813074","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}
Anchor text has a history of enriching documents for a variety of tasks within the World Wide Web. Anchor texts are useful because they are similar to typical Web queries, and because they express the document's context. Therefore, it is a common practice for Web search engines to incorporate incoming anchor text into the document's standard textual representation. However, this approach will not suffice for documents with very few inlinks, and it does not incorporate the document's full context. To mediate these problems, we employ link paths, which contain anchor texts from paths through the Web ending at the document in question. We propose and study several different ways to aggregate anchor text from link paths, and we show that the information from link paths can be used to (1) improve known item search in site-specific search, and (2) map Web pages to database records. We rigorously evaluate our proposed approach on several real world test collections. We find that our approach significantly improves performance over baseline and existing techniques in both tasks.
{"title":"Building enriched web page representations using link paths","authors":"Tim Weninger, ChengXiang Zhai, Jiawei Han","doi":"10.1145/2309996.2310006","DOIUrl":"https://doi.org/10.1145/2309996.2310006","url":null,"abstract":"Anchor text has a history of enriching documents for a variety of tasks within the World Wide Web. Anchor texts are useful because they are similar to typical Web queries, and because they express the document's context. Therefore, it is a common practice for Web search engines to incorporate incoming anchor text into the document's standard textual representation. However, this approach will not suffice for documents with very few inlinks, and it does not incorporate the document's full context. To mediate these problems, we employ link paths, which contain anchor texts from paths through the Web ending at the document in question. We propose and study several different ways to aggregate anchor text from link paths, and we show that the information from link paths can be used to (1) improve known item search in site-specific search, and (2) map Web pages to database records. We rigorously evaluate our proposed approach on several real world test collections. We find that our approach significantly improves performance over baseline and existing techniques in both tasks.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"7 1","pages":"53-62"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89590701","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}
In this paper, we investigate a methodology for measuring the influence of tag recommenders on the indexing quality in collaborative tagging systems. We propose to use the inter-resource consistency as an indicator of indexing quality. The inter-resource consistency measures the degree to which the tag vectors of indexed resources reflect how the users understand the resources. We use this methodology for evaluating how tag recommendations coming from (1) the popular tags at a resource or from (2) the user's own vocabulary influence the indexing quality. We show that recommending popular tags decreases the indexing quality and that recommending the user's own vocabulary increases the indexing quality.
{"title":"Measuring the influence of tag recommenders on the indexing quality in tagging systems","authors":"Klaas Dellschaft, Steffen Staab","doi":"10.1145/2309996.2310009","DOIUrl":"https://doi.org/10.1145/2309996.2310009","url":null,"abstract":"In this paper, we investigate a methodology for measuring the influence of tag recommenders on the indexing quality in collaborative tagging systems. We propose to use the inter-resource consistency as an indicator of indexing quality. The inter-resource consistency measures the degree to which the tag vectors of indexed resources reflect how the users understand the resources. We use this methodology for evaluating how tag recommendations coming from (1) the popular tags at a resource or from (2) the user's own vocabulary influence the indexing quality. We show that recommending popular tags decreases the indexing quality and that recommending the user's own vocabulary increases the indexing quality.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"29 1","pages":"73-82"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84256052","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}
We present a quanti-qualitative research about Trending Topics in Twitter. Our goal was to investigate how social networks can interfere in Trending Topics seeking for visibility and based on social capital, using bridging and bonding ties. We collected, analyzed and classified 460 topics from the Brazilian Trending Topics' List and the social networks associated to 40 of those. Our results point to two types of topics: artificial topics, created by groups of users consciously acting to put their message among the Trending Topics, usually to make statements and gain visibility to their causes; and organic topics, which emerge without effortful coordination by a group of people. While organic topics rely on values such as novelty and spread through bridging ties, artificial topics are based on bonding ties, with associated values such as engagement, cooperation and trust among the actors.
{"title":"On the rise of artificial trending topics in twitter","authors":"R. Recuero, Ricardo Araujo","doi":"10.1145/2309996.2310046","DOIUrl":"https://doi.org/10.1145/2309996.2310046","url":null,"abstract":"We present a quanti-qualitative research about Trending Topics in Twitter. Our goal was to investigate how social networks can interfere in Trending Topics seeking for visibility and based on social capital, using bridging and bonding ties. We collected, analyzed and classified 460 topics from the Brazilian Trending Topics' List and the social networks associated to 40 of those. Our results point to two types of topics: artificial topics, created by groups of users consciously acting to put their message among the Trending Topics, usually to make statements and gain visibility to their causes; and organic topics, which emerge without effortful coordination by a group of people. While organic topics rely on values such as novelty and spread through bridging ties, artificial topics are based on bonding ties, with associated values such as engagement, cooperation and trust among the actors.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"1 1","pages":"305-306"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86709034","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}
Luca Costabello, S. Villata, Nicolas Delaforge, Fabien L. Gandon
We present Shi3ld, a context-aware access control framework for consuming the Web of Data from mobile devices.
我们提出了shild，一个上下文感知的访问控制框架，用于从移动设备消费数据网络。
{"title":"SHI3LD: an access control framework for the mobile web of data","authors":"Luca Costabello, S. Villata, Nicolas Delaforge, Fabien L. Gandon","doi":"10.1145/2309996.2310049","DOIUrl":"https://doi.org/10.1145/2309996.2310049","url":null,"abstract":"We present Shi3ld, a context-aware access control framework for consuming the Web of Data from mobile devices.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"32 1","pages":"311-312"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86896370","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}
Eugenia-Maria Kontopoulou, Maria Predari, Thymios Kostakis, Efstratios Gallopoulos
What can graph and matrix based mathematical models tell us about ergodic literature? A digraph of storylets connected by links and the corresponding adjacency matrix encoding is used to formulate some queries regarding hypertexts of this type. It is reasoned that the Google random surfer provides a useful model for the behavior of the reader of such fiction. This motivates the use of graph and Web based metrics for ranking storylets and some other tasks. A dataset, termed childif, based on printed books from three series popular with children and young adults and its characteristics are described. Two link-based metrics, SMrank and versions of PageRank, are described and applied on childif to rank storylets. It is shown that several characteristics of these stories can be expressed as and computed with matrix operations. An interpretation of the ranking results is provided. Results on some acyclic digraphs indicate that the rankings convey useful information regarding plot development. In conclusion, using matrix and graph theoretic techniques one can extract useful information from this type of ergodic literature that would be harder to obtain by simply reading it or by examining the underlying digraph.
{"title":"Graph and matrix metrics to analyze ergodic literature for children","authors":"Eugenia-Maria Kontopoulou, Maria Predari, Thymios Kostakis, Efstratios Gallopoulos","doi":"10.1145/2309996.2310018","DOIUrl":"https://doi.org/10.1145/2309996.2310018","url":null,"abstract":"What can graph and matrix based mathematical models tell us about ergodic literature? A digraph of storylets connected by links and the corresponding adjacency matrix encoding is used to formulate some queries regarding hypertexts of this type. It is reasoned that the Google random surfer provides a useful model for the behavior of the reader of such fiction. This motivates the use of graph and Web based metrics for ranking storylets and some other tasks. A dataset, termed childif, based on printed books from three series popular with children and young adults and its characteristics are described. Two link-based metrics, SMrank and versions of PageRank, are described and applied on childif to rank storylets. It is shown that several characteristics of these stories can be expressed as and computed with matrix operations. An interpretation of the ranking results is provided. Results on some acyclic digraphs indicate that the rankings convey useful information regarding plot development. In conclusion, using matrix and graph theoretic techniques one can extract useful information from this type of ergodic literature that would be harder to obtain by simply reading it or by examining the underlying digraph.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"30 1","pages":"133-142"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77699103","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}
Tagging systems allow users to assign arbitrary text labels (i.e., tags) to various types of resources, such as photos or web pages, to facilitate future retrieval and selective sharing of contents. The resulting system of classification is referred to as a folksonomy. The uncontrolled nature of tags leads to inconsistencies in the usage of terms which impairs the utility of the system. Approaches to this problem that map tags to concepts of external knowledge representations, such as ontologies, are often inapplicable since they require that corresponding concepts exist and that they reflect the meaning of tags as intended by the users. In this paper, we present the notion of implicit tag relations. Our aim is to improve the accessibility of contents in tagging systems without significantly reducing the flexibility and universal applicability of tags. Instead of explicitly relating tags to each other, we propose to give users the ability to retroactively alter folksonomies by changing the tags of many resources with a single operation. This way, the usage of tags can be harmonized and it can be controlled how they are used in combination. We highlight the benefits of our approach compared to explicit tag relations and discuss important implications as well as its limitations.
{"title":"Structuring folksonomies with implicit tag relations","authors":"F. Matthes, C. Neubert, Alexander Steinhoff","doi":"10.1145/2309996.2310051","DOIUrl":"https://doi.org/10.1145/2309996.2310051","url":null,"abstract":"Tagging systems allow users to assign arbitrary text labels (i.e., tags) to various types of resources, such as photos or web pages, to facilitate future retrieval and selective sharing of contents. The resulting system of classification is referred to as a folksonomy. The uncontrolled nature of tags leads to inconsistencies in the usage of terms which impairs the utility of the system. Approaches to this problem that map tags to concepts of external knowledge representations, such as ontologies, are often inapplicable since they require that corresponding concepts exist and that they reflect the meaning of tags as intended by the users. In this paper, we present the notion of implicit tag relations. Our aim is to improve the accessibility of contents in tagging systems without significantly reducing the flexibility and universal applicability of tags. Instead of explicitly relating tags to each other, we propose to give users the ability to retroactively alter folksonomies by changing the tags of many resources with a single operation. This way, the usage of tags can be harmonized and it can be controlled how they are used in combination. We highlight the benefits of our approach compared to explicit tag relations and discuss important implications as well as its limitations.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"77 1","pages":"315-316"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77940534","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}
C. Trattner, Yi-ling Lin, Denis Parra, Zhen Yue, William Real, Peter Brusilovsky
The availability of social tags has greatly enhanced access to information. Tag clouds have emerged as a new "social" way to find and visualize information, providing both one-click access to information and a snapshot of the "aboutness" of a tagged collection. A range of research projects explored and compared different tag artifacts for information access ranging from regular tag clouds to tag hierarchies. At the same time, there is a lack of user studies that compare the effectiveness of different types of tag-based browsing interfaces from the users point of view. This paper contributes to the research on tag-based information access by presenting a controlled user study that compared three types of tag-based interfaces on two recognized types of search tasks -- lookup and exploratory search. Our results demonstrate that tag-based browsing interfaces significantly outperform traditional search interfaces in both performance and user satisfaction. At the same time, the differences between the two types of tag-based browsing interfaces explored in our study are not as clear.
{"title":"Evaluating tag-based information access in image collections","authors":"C. Trattner, Yi-ling Lin, Denis Parra, Zhen Yue, William Real, Peter Brusilovsky","doi":"10.1145/2309996.2310016","DOIUrl":"https://doi.org/10.1145/2309996.2310016","url":null,"abstract":"The availability of social tags has greatly enhanced access to information. Tag clouds have emerged as a new \"social\" way to find and visualize information, providing both one-click access to information and a snapshot of the \"aboutness\" of a tagged collection. A range of research projects explored and compared different tag artifacts for information access ranging from regular tag clouds to tag hierarchies. At the same time, there is a lack of user studies that compare the effectiveness of different types of tag-based browsing interfaces from the users point of view. This paper contributes to the research on tag-based information access by presenting a controlled user study that compared three types of tag-based interfaces on two recognized types of search tasks -- lookup and exploratory search. Our results demonstrate that tag-based browsing interfaces significantly outperform traditional search interfaces in both performance and user satisfaction. At the same time, the differences between the two types of tag-based browsing interfaces explored in our study are not as clear.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"41 1","pages":"113-122"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76203808","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}
F. Abel, C. Hauff, G. Houben, R.J.P. Stronkman, Ke Tao
Automatically filtering relevant information about a real-world incident from Social Web streams and making the information accessible and findable in the given context of the incident are non-trivial scientific challenges. In this paper, we engineer and evaluate solutions that analyze the semantics of Social Web data streams to solve these challenges. We introduce Twitcident, a framework and Web-based system for filtering, searching and analyzing information about real-world incidents or crises. Given an incident, our framework automatically starts tracking and filtering information that is relevant for the incident from Social Web streams and Twitter particularly. It enriches the semantics of streamed messages to profile incidents and to continuously improve and adapt the information filtering to the current temporal context. Faceted search and analytical tools allow people and emergency services to retrieve particular information fragments and overview and analyze the current situation as reported on the Social Web. We put our Twitcident system into practice by connecting it to emergency broadcasting services in the Netherlands to allow for the retrieval of relevant information from Twitter streams for any incident that is reported by those services. We conduct large-scale experiments in which we evaluate (i) strategies for filtering relevant information for a given incident and (ii) search strategies for finding particular information pieces. Our results prove that the semantic enrichment offered by our framework leads to major and significant improvements of both the filtering and the search performance. A demonstration is available via: http://wis.ewi.tudelft.nl/twitcident/
{"title":"Semantics + filtering + search = twitcident. exploring information in social web streams","authors":"F. Abel, C. Hauff, G. Houben, R.J.P. Stronkman, Ke Tao","doi":"10.1145/2309996.2310043","DOIUrl":"https://doi.org/10.1145/2309996.2310043","url":null,"abstract":"Automatically filtering relevant information about a real-world incident from Social Web streams and making the information accessible and findable in the given context of the incident are non-trivial scientific challenges. In this paper, we engineer and evaluate solutions that analyze the semantics of Social Web data streams to solve these challenges. We introduce Twitcident, a framework and Web-based system for filtering, searching and analyzing information about real-world incidents or crises. Given an incident, our framework automatically starts tracking and filtering information that is relevant for the incident from Social Web streams and Twitter particularly. It enriches the semantics of streamed messages to profile incidents and to continuously improve and adapt the information filtering to the current temporal context. Faceted search and analytical tools allow people and emergency services to retrieve particular information fragments and overview and analyze the current situation as reported on the Social Web.\u0000 We put our Twitcident system into practice by connecting it to emergency broadcasting services in the Netherlands to allow for the retrieval of relevant information from Twitter streams for any incident that is reported by those services. We conduct large-scale experiments in which we evaluate (i) strategies for filtering relevant information for a given incident and (ii) search strategies for finding particular information pieces. Our results prove that the semantic enrichment offered by our framework leads to major and significant improvements of both the filtering and the search performance. A demonstration is available via: http://wis.ewi.tudelft.nl/twitcident/","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"27 1","pages":"285-294"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73927294","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 emergence of a Web of Linked Data [2] enables new forms of application that require expressive query access, for which mature, Web-scale information retrieval techniques may not be suited. Rather than attempting to deliver expressive query capabilities at Web-scale, we propose the use of smaller, pre-populated data caches whose contents are personalized to the needs of an individual user. Such caches can act as personal data stores supporting a range of different applications. Furthermore, we discuss a user evaluation which demonstrates that our approach can accurately predict queries and their execution probability, thereby optimizing the cache population process. In this paper we formally introduce a strategy for predicting queries that can then be used to inform an a priori population of a personal cache of Linked Data harvested from Web. Based on a comprehensive user evaluation we demonstrate that our approach can accurately predict queries and their execution probability, thereby optimizing the cache population process.
{"title":"Query prediction with context models for populating personal linked data caches","authors":"O. Hartig, T. Heath","doi":"10.1145/2309996.2310056","DOIUrl":"https://doi.org/10.1145/2309996.2310056","url":null,"abstract":"The emergence of a Web of Linked Data [2] enables new forms of application that require expressive query access, for which mature, Web-scale information retrieval techniques may not be suited. Rather than attempting to deliver expressive query capabilities at Web-scale, we propose the use of smaller, pre-populated data caches whose contents are personalized to the needs of an individual user. Such caches can act as personal data stores supporting a range of different applications. Furthermore, we discuss a user evaluation which demonstrates that our approach can accurately predict queries and their execution probability, thereby optimizing the cache population process. In this paper we formally introduce a strategy for predicting queries that can then be used to inform an a priori population of a personal cache of Linked Data harvested from Web. Based on a comprehensive user evaluation we demonstrate that our approach can accurately predict queries and their execution probability, thereby optimizing the cache population process.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"203 1","pages":"325-326"},"PeriodicalIF":0.0,"publicationDate":"2012-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75715971","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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