Chirag Shah
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Publications by Chirag Shah (bibliography)
» 2009 «
Shah, Chirag, Marchionini, Gary and Kelly, Diane (2009): Learning design principles for a collaborative information seeking system. In: Proceedings of ACM CHI 2009 Conference on Human Factors in Computing Systems 2009. pp. 3419-3424. Available online
While collaboration is a natural choice in many situations, there is a lack of specialized tools for collaboratively seeking information. We present design specifications and implementation of a collaborative information seeking system. We test this system through several pilot studies and cognitive walkthroughs. User interactions and feedback from these studies help us refine our design specifications for a better collaborative information seeking system.
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» 2008 «
Capra, Robert G., Lee, Christopher A., Marchionini, Gary, Russell, Terrell, Shah, Chirag and Stutzman, Fred (2008): Selection and context scoping for digital video collections: an investigation of YouTube and blogs. In: JCDL08 Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries 2008. pp. 211-220. Available online
Digital curators are faced with decisions about what part of the ever-growing, ever-evolving space of digital information to collect and preserve. The recent explosion of web video on sites such as YouTube presents curators with an even greater challenge -- how to sort through and filter a large amount of information to find, assess and ultimately preserve important, relevant, and interesting video. In this paper, we describe research conducted to help inform digital curation of on-line video. Since May 2007, we have been monitoring the results of 57 queries on YouTube related to the 2008 U.S. presidential election. We report results comparing these data to blogs that point to candidate videos on YouTube and discuss the effects of query-based harvesting as a collection development strategy.
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Shah, Chirag (2008): TubeKit: a query-based YouTube crawling toolkit. In: JCDL08 Proceedings of the 8th ACM/IEEE-CS Joint Conference on Digital Libraries 2008. p. 433. Available online
Pickens, Jeremy, Golovchinsky, Gene, Shah, Chirag, Qvarfordt, Pernilla and Back, Maribeth (2008): Algorithmic mediation for collaborative exploratory search. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. pp. 315-322. Available online
We describe a new approach to information retrieval: algorithmic mediation for intentional, synchronous collaborative exploratory search. Using our system, two or more users with a common information need search together, simultaneously. The collaborative system provides tools, user interfaces and, most importantly, algorithmically-mediated retrieval to focus, enhance and augment the team's search and communication activities. Collaborative search outperformed post hoc merging of similarly instrumented single user runs. Algorithmic mediation improved both collaborative search (allowing a team of searchers to find relevant information more efficiently and effectively), and exploratory search (allowing the searchers to find relevant information that cannot be found while working individually).
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Shah, Chirag (2008): Understanding system implementation and user behavior in a collaborative information seeking environment. In: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2008. p. 896. Available online
» 2007 «
Shah, Chirag and Marchionini, Gary (2007): Capturing relevant information for digital curation. In: JCDL07: Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries 2007. p. 496. Available online
Shah, Chirag and Marchionini, Gary (2007): ContextMiner: a tool for digital library curators. In: JCDL07: Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries 2007. p. 514. Available online
Shah, Chirag, Kelly, Diane and Fu, Xin (2007): Making mind and machine meet: a study of combining cognitive and algorithmic relevance feedback. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 877-878. Available online
Using Saracevic's relevance types, we explore approaches to combining algorithm and cognitive relevance in a term relevance feedback scenario. Data collected from 21 users who provided relevance feedback about terms suggested by a system for 50 TREC HARD topics are used. The former type of feedback is considered as cognitive relevance and the latter type is considered as algorithm relevance. We construct retrieval runs using these two types of relevance feedback and experiment with ways of combining them with simple Boolean operators. Results show minimal differences in performance with respect to the different techniques.
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Fu, Xin, Kelly, Diane and Shah, Chirag (2007): Using collaborative queries to improve retrieval for difficult topics. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 879-880. Available online
We describe a preliminary analysis of queries created by 81 users for 4 topics from the TREC Robust Track. Our goal was to explore the potential benefits of using queries created by multiple users on retrieval performance for difficult topics. We first examine the overlap in users' queries and the overlap in results with respect to different queries for the same topic. We then explore the potential benefits of combining users' queries in various ways. Our results provide some evidence that having access to multiple users' queries can improve retrieval for individual searchers and for difficult topics.
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Shah, Chirag and Marchionini, Gary (2007): DiscoverInfo: a tool for discovering information with relevance and novelty. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. p. 902. Available online
» 2006 «
Shah, Chirag, Croft, W. Bruce and Jensen, David (2006): Representing documents with named entities for story link detection (SLD). In: Yu, Philip S., Tsotras, Vassilis J., Fox, Edward A. and Liu, Bing (eds.) Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management November 6-11, 2006, Arlington, Virginia, USA. pp. 868-869. Available online
» 2004 «
Shah, Chirag and Croft, W. Bruce (2004): Evaluating high accuracy retrieval techniques. In: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2004. pp. 2-9. Available online
Although information retrieval research has always been concerned with improving the effectiveness of search, in some applications, such as information analysis, a more specific requirement exists for high accuracy retrieval. This means that achieving high precision in the top document ranks is paramount. In this paper we present work aimed at achieving high accuracy in ad-hoc document retrieval by incorporating approaches from question answering (QA). We focus on getting the first relevant result as high as possible in the ranked list and argue that traditional precision and recall are not appropriate measures for evaluating this task. We instead use the mean reciprocal rank (MRR) of the first relevant result. We evaluate three different methods for modifying queries to achieve high accuracy. The experiments done on TREC data provide support for the approach of using MRR and incorporating QA techniques for getting high accuracy in ad-hoc retrieval task.
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Mar 16th, 2010
Changes to this page (author)
14 Feb 2010: Enabled abstracts to be shown on Chirag Shah's author page.29 May 2009: Author was edited 09 May 2009: Author was edited
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