Understanding query intent is essential to generating appropriate rankings for users. Existing methods have provided customized rankings to answer queries with different intent. While previous methods have shown improvement over their non-discriminating counterparts, the web authors' intent when creating a hyperlink is seldom taken into consideration. To mitigate this gap, we categorize hyperlinks into two types that are reasonably comparable to query intent, i.e., links describing the target page's identity and links describing the target page's content. We argue that emphasis on one type of link when ranking documents can benefit the retrieval for that type of query. We start by presenting a link intent classification approach based on the link context representations that captures evidence from anchors, target pages, and their associated links, and then introduce our enhanced retrieval model that incorporates link intent into the estimation of anchor text importance. Comparative experiments on two large scale web corpora demonstrate the efficacy of our approaches.
{"title":"Bridging link and query intent to enhance web search","authors":"Na Dai, Xiaoguang Qi, Brian D. Davison","doi":"10.1145/1995966.1995973","DOIUrl":"https://doi.org/10.1145/1995966.1995973","url":null,"abstract":"Understanding query intent is essential to generating appropriate rankings for users. Existing methods have provided customized rankings to answer queries with different intent. While previous methods have shown improvement over their non-discriminating counterparts, the web authors' intent when creating a hyperlink is seldom taken into consideration. To mitigate this gap, we categorize hyperlinks into two types that are reasonably comparable to query intent, i.e., links describing the target page's identity and links describing the target page's content. We argue that emphasis on one type of link when ranking documents can benefit the retrieval for that type of query. We start by presenting a link intent classification approach based on the link context representations that captures evidence from anchors, target pages, and their associated links, and then introduce our enhanced retrieval model that incorporates link intent into the estimation of anchor text importance. Comparative experiments on two large scale web corpora demonstrate the efficacy of our approaches.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"70 1","pages":"17-26"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86747374","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}
Heterogeneous systems in nature are often characterized by the mesoscopic structure known as communities. In this paper, we propose a framework to address the problem of community detection in bipartite networks and tripartite hypernetworks, which are appropriate models for many heterogeneous systems. The most important advantage of our method is that it is competent for detecting both communities of one-to-one correspondence and communities of many-to-many correspondence, while state of the art techniques can only handle the former. We demonstrate this advantage and show other desired properties of our method through extensive experiments in both synthetic and real-world datasets.
{"title":"Extracting the mesoscopic structure from heterogeneous systems","authors":"Xin Liu, T. Murata","doi":"10.1145/1995966.1995995","DOIUrl":"https://doi.org/10.1145/1995966.1995995","url":null,"abstract":"Heterogeneous systems in nature are often characterized by the mesoscopic structure known as communities. In this paper, we propose a framework to address the problem of community detection in bipartite networks and tripartite hypernetworks, which are appropriate models for many heterogeneous systems. The most important advantage of our method is that it is competent for detecting both communities of one-to-one correspondence and communities of many-to-many correspondence, while state of the art techniques can only handle the former. We demonstrate this advantage and show other desired properties of our method through extensive experiments in both synthetic and real-world datasets.","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":"211-220"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89280659","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}
Personalized search and browsing is increasingly vital especially for enterprises to able to reach their customers. Key challenge in supporting personalization is the need for rich metadata such as cognitive metadata about documents. As we consider size of large knowledge bases, manual annotation is not scalable and feasible. On the other hand, automatic mining of cognitive metadata is challenging since it is very difficult to understand underlying intellectual knowledge about documents automatically. To alleviate this problem, we introduce a novel metadata extraction framework, which is based on fuzzy information granulation and fuzzy inference system for automatic cognitive metadata mining. The user evaluation study shows that our approach provides reasonable precision rates for difficulty, interactivity type, and interactivity level on the examined 100 documents. In addition, proposed fuzzy inference system achieves improved results compared to a rule-based reasoner for document difficulty metadata extraction (11% improvement).
{"title":"Automatic mining of cognitive metadata using fuzzy inference","authors":"M. Şah, V. Wade","doi":"10.1145/1995966.1995975","DOIUrl":"https://doi.org/10.1145/1995966.1995975","url":null,"abstract":"Personalized search and browsing is increasingly vital especially for enterprises to able to reach their customers. Key challenge in supporting personalization is the need for rich metadata such as cognitive metadata about documents. As we consider size of large knowledge bases, manual annotation is not scalable and feasible. On the other hand, automatic mining of cognitive metadata is challenging since it is very difficult to understand underlying intellectual knowledge about documents automatically. To alleviate this problem, we introduce a novel metadata extraction framework, which is based on fuzzy information granulation and fuzzy inference system for automatic cognitive metadata mining. The user evaluation study shows that our approach provides reasonable precision rates for difficulty, interactivity type, and interactivity level on the examined 100 documents. In addition, proposed fuzzy inference system achieves improved results compared to a rule-based reasoner for document difficulty metadata extraction (11% improvement).","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"68 1","pages":"37-46"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84421710","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. Squicciarini, Smitha Sundareswaran, D. Lin, Joshua Wede
More and more people go online today and share their personal images using popular web services like Picasa. While enjoying the convenience brought by advanced technology, people also become aware of the privacy issues of data being shared. Recent studies have highlighted that people expect more tools to allow them to regain control over their privacy. In this work, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. In particular, we examine the role of image content and metadata as possible indicators of users' privacy preferences. We propose a two-level image classification framework to obtain image categories which may be associated with similar policies. Then, we develop a policy prediction algorithm to automatically generate a policy for each newly uploaded image. Most importantly, the generated policy will follow the trend of the user's privacy concerns evolved with time. We have conducted an extensive user study and the results demonstrate effectiveness of our system with the prediction accuracy around 90%.
{"title":"A3P: adaptive policy prediction for shared images over popular content sharing sites","authors":"A. Squicciarini, Smitha Sundareswaran, D. Lin, Joshua Wede","doi":"10.1145/1995966.1996000","DOIUrl":"https://doi.org/10.1145/1995966.1996000","url":null,"abstract":"More and more people go online today and share their personal images using popular web services like Picasa. While enjoying the convenience brought by advanced technology, people also become aware of the privacy issues of data being shared. Recent studies have highlighted that people expect more tools to allow them to regain control over their privacy. In this work, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. In particular, we examine the role of image content and metadata as possible indicators of users' privacy preferences. We propose a two-level image classification framework to obtain image categories which may be associated with similar policies. Then, we develop a policy prediction algorithm to automatically generate a policy for each newly uploaded image. Most importantly, the generated policy will follow the trend of the user's privacy concerns evolved with time. We have conducted an extensive user study and the results demonstrate effectiveness of our system with the prediction accuracy around 90%.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"8 1","pages":"261-270"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86425673","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}
Semantic structures, ranging from ontologies to flat folksonomies, are widely used on the Web despite the fact that their creation in sufficient quality is often a costly task. We propose a new approach for acquiring a lightweight network of related terms via the Little Search Game - a competitive browser game in search query formulation. The format of game queries forces players to express their perception of term relatedness. The term network is aggregated using "votes" from multiple players playing the same problem instance. We show that nearly 91% of the relationships produced by Little Search Game are correct and also elaborate on the game's unique ability to discover term relations, that are otherwise hidden to typical corpora mining methods.
{"title":"Little search game: term network acquisition via a human computation game","authors":"Jakub Simko, M. Tvarozek, M. Bieliková","doi":"10.1145/1995966.1995977","DOIUrl":"https://doi.org/10.1145/1995966.1995977","url":null,"abstract":"Semantic structures, ranging from ontologies to flat folksonomies, are widely used on the Web despite the fact that their creation in sufficient quality is often a costly task. We propose a new approach for acquiring a lightweight network of related terms via the Little Search Game - a competitive browser game in search query formulation. The format of game queries forces players to express their perception of term relatedness. The term network is aggregated using \"votes\" from multiple players playing the same problem instance. We show that nearly 91% of the relationships produced by Little Search Game are correct and also elaborate on the game's unique ability to discover term relations, that are otherwise hidden to typical corpora mining methods.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"12 1","pages":"57-62"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88012843","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}
People yearn for more integration of their information. But tools meant to help often do the opposite-pulling people and their information in different directions. Fragmentation is potentially worsened as personal information moves onto the Web and into a myriad of special-purpose, mobile-enabled applications. How can tool developers innovate "non-disruptively" in ways that do not force people to re-organize or re-locate their information? This paper makes two arguments: 1. An integration of personal information is not likely to happen through some new release of a desktop operating system or via a Web-based "super tool." 2. Instead, integration is best supported through the development of a standards-based infrastructure that makes provision for the shared manipulation of common structure by any number of tools, each in its own way. To illustrate this approach, the paper describes an XML-based schema, considerations in its design and its current use in three separate tools. The schema in its design and use builds on the lessons learned by the open hypermedia and structural computing communities while moving forward with new techniques that address some of the changes introduced by the evolution of the term "application" to move beyond desktop apps to mobile apps, cloud-based apps and various hybrid architectures.
{"title":"Many views, many modes, many tools ... one structure: Towards a Non-disruptive Integration of Personal Information","authors":"W. Jones, K. Anderson","doi":"10.1145/1995966.1995984","DOIUrl":"https://doi.org/10.1145/1995966.1995984","url":null,"abstract":"People yearn for more integration of their information. But tools meant to help often do the opposite-pulling people and their information in different directions. Fragmentation is potentially worsened as personal information moves onto the Web and into a myriad of special-purpose, mobile-enabled applications. How can tool developers innovate \"non-disruptively\" in ways that do not force people to re-organize or re-locate their information? This paper makes two arguments: 1. An integration of personal information is not likely to happen through some new release of a desktop operating system or via a Web-based \"super tool.\" 2. Instead, integration is best supported through the development of a standards-based infrastructure that makes provision for the shared manipulation of common structure by any number of tools, each in its own way. To illustrate this approach, the paper describes an XML-based schema, considerations in its design and its current use in three separate tools. The schema in its design and use builds on the lessons learned by the open hypermedia and structural computing communities while moving forward with new techniques that address some of the changes introduced by the evolution of the term \"application\" to move beyond desktop apps to mobile apps, cloud-based apps and various hybrid architectures.","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":"113-122"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88244404","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}
While the significance of hypertext links for the new ways of telling stories has been widely discussed, there has been not many debates about the very elements that are being connected: hypertext nodes. Apart from few exceptions, poetics of the link overshadows poetics of the node. My goal is to re-focus on a single node, or lexia, by introducing the concept of contextual regulation as the major force that shapes hypertext narrative units. Because many lexias must be capable of occurring in different contexts and at different stages of the unfolding story, several compromises have to be made on the level of language, style, plot and discourse. Each node, depending on its position and importance, has a varying level of connectivity and autonomy, which affects the global coherence of text. After focusing on relations between the notion of lexia (as a coherent and flexible unit) and the notion of kernel in narrative theory, an explanation of rules behind contextual regulation is presented, along with the basic typology of nodes. Then an attempt to enhance existing plot pools for hypertext fiction is undertaken. Several suggestions for the new plots, offered by the node-centered approach, are introduced.
{"title":"New plots for hypertext?: towards poetics of a hypertext node","authors":"Mariusz Pisarski","doi":"10.1145/1995966.1996007","DOIUrl":"https://doi.org/10.1145/1995966.1996007","url":null,"abstract":"While the significance of hypertext links for the new ways of telling stories has been widely discussed, there has been not many debates about the very elements that are being connected: hypertext nodes. Apart from few exceptions, poetics of the link overshadows poetics of the node. My goal is to re-focus on a single node, or lexia, by introducing the concept of contextual regulation as the major force that shapes hypertext narrative units. Because many lexias must be capable of occurring in different contexts and at different stages of the unfolding story, several compromises have to be made on the level of language, style, plot and discourse. Each node, depending on its position and importance, has a varying level of connectivity and autonomy, which affects the global coherence of text.\u0000 After focusing on relations between the notion of lexia (as a coherent and flexible unit) and the notion of kernel in narrative theory, an explanation of rules behind contextual regulation is presented, along with the basic typology of nodes. Then an attempt to enhance existing plot pools for hypertext fiction is undertaken. Several suggestions for the new plots, offered by the node-centered approach, are introduced.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"10 1","pages":"313-318"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86839940","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}
Y. Takahashi, H. Ohshima, Mitsuo Yamamoto, H. Iwasaki, S. Oyama, Katsumi Tanaka
We propose a method to evaluate the significance of historical entities (people, events, and so on.). Here, the significance of a historical entity means how it affected other historical entities. Our proposed method first calculates the tempo-spacial impact of historical entities. The impact of a historical entity varies according to time and location. Historical entities are collected from Wikipedia. We assume that a Wikipedia link between historical entities represents an impact propagation. That is, when an entity has a link to another entity, we regard the former is influenced by the latter. Historical entities in Wikipedia usually have the date and location of their occurrence. Our proposed iteration algorithm propagates such initial tempo-spacial information through links in the similar manner as PageRank, so the tempo-spacial impact scores of all the historical entities can be calculated. We assume that a historical entity is significant if it influences many other entities that are far from it temporally or geographically. We demonstrate a prototype system and show the results of experiments that prove the effectiveness of our method.
{"title":"Evaluating significance of historical entities based on tempo-spatial impacts analysis using Wikipedia link structure","authors":"Y. Takahashi, H. Ohshima, Mitsuo Yamamoto, H. Iwasaki, S. Oyama, Katsumi Tanaka","doi":"10.1145/1995966.1995980","DOIUrl":"https://doi.org/10.1145/1995966.1995980","url":null,"abstract":"We propose a method to evaluate the significance of historical entities (people, events, and so on.). Here, the significance of a historical entity means how it affected other historical entities. Our proposed method first calculates the tempo-spacial impact of historical entities. The impact of a historical entity varies according to time and location. Historical entities are collected from Wikipedia. We assume that a Wikipedia link between historical entities represents an impact propagation. That is, when an entity has a link to another entity, we regard the former is influenced by the latter. Historical entities in Wikipedia usually have the date and location of their occurrence. Our proposed iteration algorithm propagates such initial tempo-spacial information through links in the similar manner as PageRank, so the tempo-spacial impact scores of all the historical entities can be calculated. We assume that a historical entity is significant if it influences many other entities that are far from it temporally or geographically. We demonstrate a prototype system and show the results of experiments that prove the effectiveness of our method.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"96 1","pages":"83-92"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80514761","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}
This paper presents GALE, the GRAPPLE Adaptive Learning Environment, which (contrary to what the word suggests) is a truly generic and general purpose adaptive hypermedia engine. Five years have passed since "The Design of AHA!" was published at ACM Hypertext (2006). GALE takes the notion of general-purpose a whole lot further. We solve shortcomings of existing adaptive systems in terms of genericity, extensibility and usability and show how GALE improves on the state of the art in all these aspects. We illustrate different authoring styles for GALE, including the use of template pages, and show how adaptation can be defined in a completely decentralized way by using the open corpus adaptation facility of GALE. GALE has been used in a number of adaptive hypermedia workshops and assignments to test whether authors can actually make use of the extensive functionality that GALE offers. Adaptation has been added to wiki sites, existing material e.g. from w3schools, and of course also to locally authored hypertext. Soon GALE will be used in cross-course adaptation at the TU/e in a pilot project to improve the success rate of university students.
{"title":"GALE: a highly extensible adaptive hypermedia engine","authors":"D. Smits, P. D. Bra","doi":"10.1145/1995966.1995978","DOIUrl":"https://doi.org/10.1145/1995966.1995978","url":null,"abstract":"This paper presents GALE, the GRAPPLE Adaptive Learning Environment, which (contrary to what the word suggests) is a truly generic and general purpose adaptive hypermedia engine. Five years have passed since \"The Design of AHA!\" was published at ACM Hypertext (2006). GALE takes the notion of general-purpose a whole lot further. We solve shortcomings of existing adaptive systems in terms of genericity, extensibility and usability and show how GALE improves on the state of the art in all these aspects. We illustrate different authoring styles for GALE, including the use of template pages, and show how adaptation can be defined in a completely decentralized way by using the open corpus adaptation facility of GALE. GALE has been used in a number of adaptive hypermedia workshops and assignments to test whether authors can actually make use of the extensive functionality that GALE offers. Adaptation has been added to wiki sites, existing material e.g. from w3schools, and of course also to locally authored hypertext. Soon GALE will be used in cross-course adaptation at the TU/e in a pilot project to improve the success rate of university students.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"82 1","pages":"63-72"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83632476","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}
Community Question Answering (CQA) websites, which archive millions of questions and answers created by CQA users to provide a rich resource of information that is missing at web search engines and QA websites, have become increasingly popular. Web users who search for answers to their questions at CQA websites, however, are often required to either (i) wait for days until other CQA users post answers to their questions which might even be incorrect, offensive, or spam, or (ii) deal with restricted answer sets created by CQA websites due to the exact-match constraint that is employed and imposed between archived questions and user-formulated questions. To automate and enhance the process of locating high-quality answers to a user's question Q at a CQA website, we introduce a CQA refinement system, called QAR. Given Q, QAR first retrieves a set of CQA questions QS that are the same as, or similar to, Q in terms of its specified information need. Thereafter, QAR selects as answers to Q the top-ranked answers (among the ones to the questions in QS) based on various similarity scores and the length of the answers. Empirical studies, which were conducted using questions provided by the Text Retrieval Conference (TREC) and Text Analysis Conference (TAC), in addition to more than four millions questions (and their corresponding answers) extracted from Yahoo! Answers, show that QAR is effective in locating archived answers, if they exist, that satisfy the information need specified in Q. We have further assessed the performance of QAR by comparing its question-matching and answer-ranking strategies with their Yahoo! Answers' counterparts and verified that QAR outperforms Yahoo! Answers in (i) locating the set of questions QS that have the highest degrees of similarity with Q and (ii) ranking archived answers to QS as answers to Q.
{"title":"A community question-answering refinement system","authors":"M. S. Pera, Yiu-Kai Ng","doi":"10.1145/1995966.1995999","DOIUrl":"https://doi.org/10.1145/1995966.1995999","url":null,"abstract":"Community Question Answering (CQA) websites, which archive millions of questions and answers created by CQA users to provide a rich resource of information that is missing at web search engines and QA websites, have become increasingly popular. Web users who search for answers to their questions at CQA websites, however, are often required to either (i) wait for days until other CQA users post answers to their questions which might even be incorrect, offensive, or spam, or (ii) deal with restricted answer sets created by CQA websites due to the exact-match constraint that is employed and imposed between archived questions and user-formulated questions. To automate and enhance the process of locating high-quality answers to a user's question Q at a CQA website, we introduce a CQA refinement system, called QAR. Given Q, QAR first retrieves a set of CQA questions QS that are the same as, or similar to, Q in terms of its specified information need. Thereafter, QAR selects as answers to Q the top-ranked answers (among the ones to the questions in QS) based on various similarity scores and the length of the answers. Empirical studies, which were conducted using questions provided by the Text Retrieval Conference (TREC) and Text Analysis Conference (TAC), in addition to more than four millions questions (and their corresponding answers) extracted from Yahoo! Answers, show that QAR is effective in locating archived answers, if they exist, that satisfy the information need specified in Q. We have further assessed the performance of QAR by comparing its question-matching and answer-ranking strategies with their Yahoo! Answers' counterparts and verified that QAR outperforms Yahoo! Answers in (i) locating the set of questions QS that have the highest degrees of similarity with Q and (ii) ranking archived answers to QS as answers to Q.","PeriodicalId":91270,"journal":{"name":"HT ... : the proceedings of the ... ACM Conference on Hypertext and Social Media. ACM Conference on Hypertext and Social Media","volume":"8 1","pages":"251-260"},"PeriodicalIF":0.0,"publicationDate":"2011-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78869575","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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