ABSTRACT
Whether figuring out where to eat in an unfamiliar city or deciding which apartment to live in, consumer generated data (i.e. reviews and forum posts) are often an important influence in online decision making. To make sense of these rich repositories of diverse opinions, searchers need to sift through a large number of reviews to characterize each item based on aspects that they care about. We introduce a novel system, SearchLens, where searchers build up a collection of "Lenses" that reflect their different latent interests, and compose the Lenses to find relevant items across different contexts. Based on the Lenses, SearchLens generates personalized interfaces with visual explanations that promotes transparency and enables deeper exploration. While prior work found searchers may not wish to put in effort specifying their goals without immediate and sufficient benefits, results from a controlled lab study suggest that our approach incentivized participants to express their interests more richly than in a baseline condition, and a field study showed that participants found benefits in SearchLens while conducting their own tasks.
- Jae-wook Ahn and Peter Brusilovsky. 2009. Adaptive visualization of search results: Bringing user models to visual analytics. Information Visualization 8, 3 (2009), 167--179. Google ScholarDigital Library
- Jae-wook Ahn, Peter Brusilovsky, Jonathan Grady, Daqing He, and Sue Yeon Syn. 2007. Open user profiles for adaptive news systems: help or harm?. In Proceedings of the 16th international conference on World Wide Web. ACM, 11--20. Google ScholarDigital Library
- Nicholas J Belkin, Colleen Cool, Judy Jeng, Amymarie Keller, Diane Kelly, Ja-Young Kim, Hyuk-Jin Lee, Muh-Chyun (Morris) Tang, and Xiao-Jun Yuan. 2001. Rutgers' TREC 2001 interactive track experience. In TREC.Google Scholar
- Nicholas J Belkin, Diane Kelly, G Kim, J-Y Kim, H-J Lee, Gheorghe Muresan, M-C Tang, X-J Yuan, and Colleen Cool. 2003. Query length in interactive information retrieval. In Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval. ACM, 205--212. Google ScholarDigital Library
- Steven Bird and Edward Loper. 2004. NLTK: the natural language toolkit. In Proceedings of the ACL 2004 on Interactive poster and demonstration sessions. Association for Computational Linguistics, 31. Google ScholarDigital Library
- Christine Susan Bruce. 1999. Workplace experiences of information literacy. International journal of information management 19, 1 (1999), 33--47. Google ScholarDigital Library
- Chris Burges, Tal Shaked, Erin Renshaw, Ari Lazier, Matt Deeds, Nicole Hamilton, and Greg Hullender. 2005. Learning to rank using gradient descent. In Proceedings of the 22nd international conference on Machine learning. ACM, 89--96. Google ScholarDigital Library
- Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, and Hang Li. 2007. Learning to rank: from pairwise approach to listwise approach. In Proceedings of the 24th international conference on Machine learning. ACM, 129--136. Google ScholarDigital Library
- Joseph Chee Chang, Saleema Amershi, and Ece Kamar. 2017. Revolt: Collaborative Crowdsourcing for Labeling Machine Learning Datasets. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, New York, NY, USA. Google ScholarDigital Library
- Joseph Chee Chang, Aniket Kittur, and Nathan Hahn. 2016. Alloy: Clustering with crowds and computation. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 3180--3191. Google ScholarDigital Library
- Liren Chen and Katia Sycara. 1998. WebMate: A personal agent for browsing and searching. In Proceedings of the second international conference on Autonomous agents. ACM, 132--139. Google ScholarDigital Library
- Nan-Chen Chen, Jina Suh, Johan Verwey, Gonzalo Ramos, Steven Drucker, and Patrice Simard. 2018. AnchorViz: Facilitating Classifier Error Discovery through Interactive Semantic Data Exploration. In 23rd International Conference on Intelligent User Interfaces. ACM, 269--280. Google ScholarDigital Library
- Lydia B Chilton, Greg Little, Darren Edge, Daniel S Weld, and James A Landay. 2013. Cascade: Crowdsourcing taxonomy creation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1999--2008. Google ScholarDigital Library
- Jason Chuang, Daniel Ramage, Christopher Manning, and Jeffrey Heer. {n. d.}. Interpretation and trust: Designing model-driven visualizations for text analysis. In Proc. CHI 2012. ACM, 443--452. Google ScholarDigital Library
- Bart De Langhe, Philip M Fernbach, and Donald R Lichtenstein. 2015. Navigating by the stars: Investigating the actual and perceived validity of online user ratings. Journal of Consumer Research 42, 6 (2015), 817--833.Google ScholarCross Ref
- Cecilia di Sciascio, Peter Brusilovsky, and Eduardo Veas. 2018. A Study on User-Controllable Social Exploratory Search. In 23rd International Conference on Intelligent User Interfaces. ACM, 353--364. Google ScholarDigital Library
- Cecilia di Sciascio, Vedran Sabol, and Eduardo E Veas. 2016. Rank as you go: User-driven exploration of search results. In Proceedings of the 21st International Conference on Intelligent User Interfaces. ACM, 118--129. Google ScholarDigital Library
- James Fogarty, Desney Tan, Ashish Kapoor, and Simon Winder. 2008. CueFlik: interactive concept learning in image search. In Proceedings of the sigchi conference on human factors in computing systems. ACM, 29--38. Google ScholarDigital Library
- Kristofer Franzen and Jussi Karlgren. 2000. Verbosity and interface design. SICS Research Report (2000).Google Scholar
- G. W. Furnas. 1986. Generalized Fisheye Views. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '86). ACM, New York, NY, USA, 16--23. Google ScholarDigital Library
- Qiwei Gan, Qing Cao, and Donald Jones. 2012. Helpfulness of online user reviews: More is less. (2012).Google Scholar
- Nathan Hahn, Joseph Chang, Ji Eun Kim, and Aniket Kittur. 2016. The Knowledge Accelerator: Big picture thinking in small pieces. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 2258--2270. Google ScholarDigital Library
- Marti Hearst. 2006. Design recommendations for hierarchical faceted search interfaces. In ACM SIGIR workshop on faceted search. Seattle, WA, 1--5.Google Scholar
- Marti Hearst, Ame Elliott, Jennifer English, Rashmi Sinha, Kirsten Swearingen, and Ka-Ping Yee. 2002. Finding the flow in web site search. Commun. ACM 45, 9 (2002), 42--49. Google ScholarDigital Library
- Marti A Hearst. 2006. Clustering versus faceted categories for information exploration. Commun. ACM 49, 4 (2006), 59--61. Google ScholarDigital Library
- Marti A Hearst and Jan O Pedersen. 1996. Reexamining the cluster hypothesis: scatter/gather on retrieval results. In Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, 76--84. Google ScholarDigital Library
- Marti A Hearst and Jan O Pedersen. 1996. Visualizing information retrieval results: a demonstration of the TileBar interface. In Conference Companion on Human Factors in Computing Systems. ACM, 394--395. Google ScholarDigital Library
- Orland Hoeber and Xue Dong Yang. 2006. A comparative user study of web search interfaces: HotMap, Concept Highlighter, and Google. In Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on. IEEE, 866--874. Google ScholarDigital Library
- Yelp Inc. 2016. The Yelp Dataset Challenge: Discover what insights lie hidden in our data. https://www.yelp.com/dataset/challenge. Accessed: 2017-09-10.Google Scholar
- Bernard J Jansen, Amanda Spink, and Tefko Saracevic. 2000. Real life, real users, and real needs: a study and analysis of user queries on the web. Information processing & management 36, 2 (2000), 207--227. Google ScholarDigital Library
- Bryan Jurish and Kay-Michael Würzner. 2013. Word and Sentence Tokenization with Hidden Markov Models. JLCL 28, 2 (2013), 61--83.Google Scholar
- Weize Kong and James Allan. 2014. Extending faceted search to the general web. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management. ACM, 839--848. Google ScholarDigital Library
- Todd Kulesza, Saleema Amershi, Rich Caruana, Danyel Fisher, and Denis Charles. 2014. Structured labeling for facilitating concept evolution in machine learning. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 3075--3084. Google ScholarDigital Library
- Julian McAuley and Jure Leskovec. 2013. Hidden factors and hidden topics: understanding rating dimensions with review text. In Proceedings of the 7th ACM conference on Recommender systems. ACM, 165--172. Google ScholarDigital Library
- Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013).Google Scholar
- Susan M Mudambi and David Schuff. 2010. Research note: What makes a helpful online review? A study of customer reviews on Amazon. com. MIS quarterly (2010), 185--200. Google ScholarDigital Library
- Jaakko Peltonen, Kseniia Belorustceva, and Tuukka Ruotsalo. 2017. Topic-Relevance Map: Visualization for Improving Search Result Comprehension. In Proceedings of the 22nd International Conference on Intelligent User Interfaces. ACM, 611--622. Google ScholarDigital Library
- Jaakko Peltonen, Jonathan Strahl, and Patrik Floréen. 2017. Negative Relevance Feedback for Exploratory Search with Visual Interactive Intent Modeling. In Proceedings of the 22nd International Conference on Intelligent User Interfaces. ACM, 149--159. Google ScholarDigital Library
- Radim Rehurek and Petr Sojka. 2010. Software Framework for Topic Modelling with Large Corpora. In Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks. ELRA, Valletta, Malta, 45--50. http://is.muni.cz/publication/884893/en.Google Scholar
- Stephen Robertson, Hugo Zaragoza, et al. 2009. The probabilistic relevance framework: BM25 and beyond. Foundations and Trends® in Information Retrieval 3, 4 (2009), 333--389. Google ScholarDigital Library
- Yong Rui, Thomas S Huang, Michael Ortega, and Sharad Mehrotra. 1998. Relevance feedback: a power tool for interactive content-based image retrieval. IEEE Transactions on circuits and systems for video technology 8, 5 (1998), 644--655. Google ScholarDigital Library
- Gerard Salton and Chris Buckley. 1990. Improving retrieval performance by relevance feedback. Journal of the American society for information science 41, 4 (1990), 288--297.Google ScholarCross Ref
- Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. 2001. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th international conference on World Wide Web. ACM, 285--295. Google ScholarDigital Library
- Xuehua Shen, Bin Tan, and ChengXiang Zhai. 2005. Implicit user modeling for personalized search. In Proceedings of the 14th ACM international conference on Information and knowledge management. ACM, 824--831. Google ScholarDigital Library
- Mirco Speretta and Susan Gauch. 2005. Personalized search based on user search histories. In Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on. IEEE, 622--628. Google ScholarDigital Library
- Jaime Teevan, Susan T Dumais, and Zachary Gutt. 2008. Challenges for supporting faceted search in large, heterogeneous corpora like the web. Proceedings of HCIR 2008 (2008), 87.Google Scholar
- Frank Van Ham and Adam Perer. 2009. "Search, show context, expand on demand": supporting large graph exploration with degree-of-interest. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009). Google ScholarDigital Library
- Cornelis J Van Rijsbergen, Stephen Edward Robertson, and Martin F Porter. 1980. New models in probabilistic information retrieval. British Library Research and Development Department London.Google Scholar
- Ho Chung Wu, Robert Wing Pong Luk, Kam Fai Wong, and Kui Lam Kwok. 2008. Interpreting tf-idf term weights as making relevance decisions. ACM Transactions on Information Systems (TOIS) 26, 3 (2008), 13. Google ScholarDigital Library
- Jinxi Xu and W Bruce Croft. 1996. Query expansion using local and global document analysis. In Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, 4--11. Google ScholarDigital Library
- Beverly Yang and Glen Jeh. 2006. Retroactive answering of search queries. In Proceedings of the 15th international conference on World Wide Web. ACM, 457--466. Google ScholarDigital Library
- David Yarowsky. 1995. Unsupervised word sense disambiguation rivaling supervised methods. In Proceedings of the 33rd annual meeting on Association for Computational Linguistics. Association for Computational Linguistics, 189--196. Google ScholarDigital Library
- Ka-Ping Yee, Kirsten Swearingen, Kevin Li, and Marti Hearst. 2003. Faceted metadata for image search and browsing. In Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 401--408. Google ScholarDigital Library
- Oren Zamir and Oren Etzioni. 1999. Grouper: a dynamic clustering interface to Web search results. Computer Networks 31, 11 (1999), 1361--1374. Google ScholarDigital Library
- Hua-Jun Zeng, Qi-Cai He, Zheng Chen, Wei-Ying Ma, and Jinwen Ma. 2004. Learning to cluster web search results. In Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval. ACM, 210--217. Google ScholarDigital Library
Index Terms
- SearchLens: composing and capturing complex user interests for exploratory search
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