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An Effective Question Expanding Method for Question Classification in cQA services cQA服务中问题分类的有效问题展开方法
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668050
Kyoungman Bae, Youngjoong Ko
{"title":"An Effective Question Expanding Method for Question Classification in cQA services","authors":"Kyoungman Bae, Youngjoong Ko","doi":"10.1145/2663714.2668050","DOIUrl":"https://doi.org/10.1145/2663714.2668050","url":null,"abstract":"This paper introduces a new question expanding method for question classification in cQA services. Input questions are mostly generated by a small size of text in the cQA services, and test inputs consist of only a question whereas training data do a pair of question and answer. Thus, the input questions cannot provide enough information for good classification in many cases. To solve this problem, we propose the question expanding method by pseudo relevant feedback and automatic answer generation. For pseudo relevant feedback, we first find relevant question-answer pairs related to an input question using the Indri search engine, and then top relevant words are chosen as expanded words. The automatic answer generation tries to create pseudo answers by adding question-related words using translation probabilities from questions to answers by Giza++. As a result, we obtain the significant improved performances when two approaches are effectively combined.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124613561","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}
引用次数: 4
Linking Today's Wikipedia and News from the Past 链接今天的维基百科和过去的新闻
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668048
Arunav Mishra
{"title":"Linking Today's Wikipedia and News from the Past","authors":"Arunav Mishra","doi":"10.1145/2663714.2668048","DOIUrl":"https://doi.org/10.1145/2663714.2668048","url":null,"abstract":"In this paper we propose a novel task of automatically linking Wikipedia excerpts describing events to past news articles. Constantly evolving Wikipedia articles tend to summarize past events by abstracting fine-grained details that mattered when the event happened. On the other hand, contemporary news articles provide details of events, as they had happened. With connections between these two orthogonal information sources in place, a user could jump between them to acquire a holistic view on past events. We cast the linking problems into two retrieval tasks and propose a single framework for addressing them. In addition, we delineate challenges involved in both these tasks and propose a framework to address these challenges. To build a better understanding of the problem, we initially consider the simpler task of linking Wikipedia events that are systematically curated into years, decades and centuries, to relevant news articles from the past. These events come with a short textual description and a date indicating when the event happened. We present a two-stage cascade approach that leverages the temporal information associated to a given event for improving the linking effectiveness. We additionally design several baselines and show that our approach outperforms all the baselines. Through the results of studying the simplified task we come a step closer to solving the larger problem proposed in this paper. As future work, we plan to build an automatic linking system that answers to the challenges identified in this paper.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121732175","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}
引用次数: 5
Two Phases Outlier Detection in Different Subspaces 不同子空间的两相离群点检测
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668046
Zhana Bao, W. Kameyama
{"title":"Two Phases Outlier Detection in Different Subspaces","authors":"Zhana Bao, W. Kameyama","doi":"10.1145/2663714.2668046","DOIUrl":"https://doi.org/10.1145/2663714.2668046","url":null,"abstract":"Mining high dimensional outlier is not fully resolved for its dimensional particularity. The existing full space based methods can find distinct outliers and neglect those hidden in some subspaces. Subspace based approaches can detect most outliers that are apparent in low dimensional spaces, while missing the invisible outliers in subspaces. This paper proposes a novel two-phase inspection model. The first phase measures neighbor's density in subspaces to find low dimensional outliers. The second phase evaluates deviation degree of neighbors in connected subspaces. The undiscovered outliers appear a fast dispersion and scatter more than its neighbors. We analysis two-phase results statistically, and merge into one score for each object. The outliers are expressed with top score objects. The evaluation on synthetic and real data sets shows that our proposal outperform state of the art algorithms in high dimensional outlier issue.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128160197","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}
引用次数: 1
Facilitating Interactive Mining of Global and Local Association Rules 促进全局和局部关联规则的交互式挖掘
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668053
Abhishek Mukherji, Elke A. Rundensteiner, M. Ward
{"title":"Facilitating Interactive Mining of Global and Local Association Rules","authors":"Abhishek Mukherji, Elke A. Rundensteiner, M. Ward","doi":"10.1145/2663714.2668053","DOIUrl":"https://doi.org/10.1145/2663714.2668053","url":null,"abstract":"Association rule mining, a critical technology for decision making, faces two key challenges: (a.) performance: unacceptably high response times that are not capable of supporting interactive analysis, and (b.) usability: lack of support for sense-making of rule relationships. In this paper I describe two solutions proposed in my dissertation research that tackle these challenges. Our proposed COLARM system addresses the online mining of local association rules. Further, our proposed PARAS and FIRE systems provide solutions for interactive mining of global association rules. Overall, this research encompasses contributions at the intersection of data mining, knowledge management and visual analytics.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134269279","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}
引用次数: 1
Supporting Exploratory Search Through Interaction Modeling 通过交互建模支持探索性搜索
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668049
Kumaripaba Athukorala
{"title":"Supporting Exploratory Search Through Interaction Modeling","authors":"Kumaripaba Athukorala","doi":"10.1145/2663714.2668049","DOIUrl":"https://doi.org/10.1145/2663714.2668049","url":null,"abstract":"With the explosive growth of information available in the Web, locating needed and relevant information remains a difficult task, whether the information is textual or visual. Although information retrieval techniques have improved a lot in providing relevant information, exploratory information search still remains difficult due to its inherently open-ended and dynamic nature. Modeling the user behavior and predicting dynamically changing information needs in exploratory search is hard. Over the past decade there has been increasing attention on rich user interfaces, retrieval techniques, and studies of exploratory search. However, existing work does not yet support the dynamic aspects of exploratory search. The objective of this research is to understand how user interaction modeling can be applied to provide better support in exploratory search tasks. In this research, we focus on building user models that can predict user intent in search using only implicit interactions with search results. One outcome of this research is a personalized search tool that predicts user intent with implicit interactions and dynamically adjusts search results.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132146230","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}
引用次数: 1
On Efficient Query Processing with the Earth Mover's Distance 基于推土机距离的高效查询处理
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668047
M. S. Uysal, C. Beecks, T. Seidl
{"title":"On Efficient Query Processing with the Earth Mover's Distance","authors":"M. S. Uysal, C. Beecks, T. Seidl","doi":"10.1145/2663714.2668047","DOIUrl":"https://doi.org/10.1145/2663714.2668047","url":null,"abstract":"The Earth Mover's Distance which is proposed in computer vision as a distance-based similarity model has been widely used and investigated in various domains for similarity search. Although there exists the opportunity to apply this well-known similarity model reflecting the human perceptual similarity both on feature histograms and signatures as feature representation techniques, efficiency improvement approaches towards the Earth Mover's Distance were often investigated on feature histograms. Thus, it can be brought into question how k-nearest-neighbor queries can be processed efficiently by using this distance-based similarity model in a database of feature signatures, such as in a multimedia database. In this paper, the work in progress is presented regarding the new lower bound Independent Minimization for Signatures (IM-Sig) to the Earth Mover's Distance on feature signatures as an efficient filter approximation approach. Furthermore, the problems and challenging issues regarding efficient query processing on feature signatures are presented. The ongoing experimental evaluation on real data points out the high efficiency of the proposed lower bound, contributing to a promising start in the research field of efficient query processing with the Earth Mover's Distance.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121420685","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}
引用次数: 6
Applications of Rule Mining in Knowledge Bases 规则挖掘在知识库中的应用
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668052
Luis Galárraga
{"title":"Applications of Rule Mining in Knowledge Bases","authors":"Luis Galárraga","doi":"10.1145/2663714.2668052","DOIUrl":"https://doi.org/10.1145/2663714.2668052","url":null,"abstract":"The continuous progress of Information Extraction (IE) techniques has led to the construction of large Knowledge Bases (KBs) containing facts about millions of entities such as people, organizations and places. KBs are important nowadays because they allow computers to understand the real world and are used in multiple domains and applications. Furthermore, the discovery of useful and non-trivial patterns in KBs, known as rule mining, opens the door for multiple applications in the areas of data analysis, prediction and automatic data engineering. In this article we present an overview of our ongoing work on rule mining on KBs and some of its applications. The scale of current KBs as well as their inherent incompleteness and noise make this endevour challenging.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125762212","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}
引用次数: 3
Two-way Recommendation Methods for Social Networks 面向社交网络的双向推荐方法
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668054
R. Nayak
{"title":"Two-way Recommendation Methods for Social Networks","authors":"R. Nayak","doi":"10.1145/2663714.2668054","DOIUrl":"https://doi.org/10.1145/2663714.2668054","url":null,"abstract":"In this work, we present the challenges associated with the two-way recommendation methods in social networks and the solutions. We discuss them from the perspective of community-type social networks such as online dating networks.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127050948","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}
引用次数: 0
Towards Robust & Reusable Evaluation for Novelty & Diversity 面向新颖性和多样性的稳健和可重用评估
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2014-11-03 DOI: 10.1145/2663714.2668045
Kai Hui
{"title":"Towards Robust & Reusable Evaluation for Novelty & Diversity","authors":"Kai Hui","doi":"10.1145/2663714.2668045","DOIUrl":"https://doi.org/10.1145/2663714.2668045","url":null,"abstract":"Existing IR measures for offline evaluation directly bring in the labels into computation, where the labels are on the entire documents. This direct dependency makes the measure highly reliant on the completeness of the labels, consequently the measure values are sensitive towards missing labels, resulting in poor robustness and reusability. To mitigate this, we propose a novel evaluation approach, constructing an intermediate layer between the labels and the measure, improving the robustness and reusability by dampening the direct dependency, as well as considering the content of the document in the measure computation. In particular, we propose to estimate a language model based on a selected relevant document set to construct a ground truth, afterward using the divergence between the search result and this ground truth to compute measures. To further save labeling efforts and to improve efficiency, we select representative documents, query set and topic terms involved in the evaluation separately before computing the measure. Preliminary experiments on the diversity tasks of TREC Web Track 2009-2012, using ClueWeb09-A as a document collection, show that with as little as 30% of judgments our novel approach almost accurately reconstructs the original system rankings determined by α-nDCG, ERR-IA, and NRBP.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130391374","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}
引用次数: 1
Data visualization and relevance feedback applied to information retrieval 数据可视化与关联反馈在信息检索中的应用
Ph.D. Workshop on Information and Knowledge Management Pub Date : 2013-11-01 DOI: 10.1145/2513166.2513178
Diogo Oliveira de Melo, A. Lopes
{"title":"Data visualization and relevance feedback applied to information retrieval","authors":"Diogo Oliveira de Melo, A. Lopes","doi":"10.1145/2513166.2513178","DOIUrl":"https://doi.org/10.1145/2513166.2513178","url":null,"abstract":"The World Wide Web is a very large source of data growing steadily and fast. In this scenario, information retrieval systems are of key importance to allow people to obtain desired information. This article proposes an information retrieval framework which employs data visualization with relevance feedback to support user interaction. Data visualization is useful to display more information about retrieved results in an intuitive manner, while relevance feedback is used to provide more results similar to those considered relevant by the user. This article presents such information retrieval framework and the Amuzi system built as proof of concept.","PeriodicalId":148359,"journal":{"name":"Ph.D. Workshop on Information and Knowledge Management","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125079945","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}
引用次数: 4
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