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Rosie Jones

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Publications by Rosie Jones (bibliography)

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» 2008 «

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Jones, Rosie, Kumar, Ravi, Pang, Bo and Tomkins, Andrew (2008): Vanity fair: privacy in querylog bundles. In: Shanahan, James G., Amer-Yahia, Sihem, Manolescu, Ioana, Zhang, Yi, Evans, David A., Kolcz, Aleksander, Choi, Key-Sun and Chowdhury, Abdur (eds.) Proceedings of the 17th ACM Conference on Information and Knowledge Management - CIKM 2008 October 26-30, 2008, Napa Valley, California, USA. pp. 853-862. Available online

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Jones, Rosie and Klinkner, Kristina Lisa (2008): Beyond the session timeout: automatic hierarchical segmentation of search topics in query logs. In: Shanahan, James G., Amer-Yahia, Sihem, Manolescu, Ioana, Zhang, Yi, Evans, David A., Kolcz, Aleksander, Choi, Key-Sun and Chowdhury, Abdur (eds.) Proceedings of the 17th ACM Conference on Information and Knowledge Management - CIKM 2008 October 26-30, 2008, Napa Valley, California, USA. pp. 699-708. Available online

» 2007 «

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Teevan, Jaime, Adar, Eytan, Jones, Rosie and Potts, Michael A. S. (2007): Information re-retrieval: repeat queries in Yahoo's logs. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 151-158. Available online

People often repeat Web searches, both to find new information on topics they have previously explored and to re-find information they have seen in the past. The query associated with a repeat search may differ from the initial query but can nonetheless lead to clicks on the same results. This paper explores repeat search behavior through the analysis of a one-year Web query log of 114 anonymous users and a separate controlled survey of an additional 119 volunteers. Our study demonstrates that as many as 40% of all queries are re-finding queries. Re-finding appears to be an important behavior for search engines to explicitly support, and we explore how this can be done. We demonstrate that changes to search engine results can hinder re-finding, and provide a way to automatically detect repeat searches and predict repeat clicks.

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Zhang, Wei Vivian, He, Xiaofei, Rey, Benjamin and Jones, Rosie (2007): Query rewriting using active learning for sponsored search. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2007. pp. 853-854. Available online

Sponsored search is a major revenue source for search companies. Web searchers can issue any queries, while advertisement keywords are limited. Query rewriting technique effectively matches user queries with relevant advertisement keywords, thus increases the amount of web advertisements available. The match relevance is critical for clicks. In this study, we aim to improve query rewriting relevance. For this purpose, we use an active learning algorithm called Transductive Experimental Design to select the most informative samples to train the query rewriting relevance model. Experiments show that this approach significantly improves model accuracy and rewriting relevance.

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Jones, Rosie and Diaz, Fernando (2007): Temporal profiles of queries. In ACM Transactions on Information Systems, 25 (3) p. 14

Documents with timestamps, such as email and news, can be placed along a timeline. The timeline for a set of documents returned in response to a query gives an indication of how documents relevant to that query are distributed in time. Examining the timeline of a query result set allows us to characterize both how temporally dependent the topic is, as well as how relevant the results are likely to be. We outline characteristic patterns in query result set timelines, and show experimentally that we can automatically classify documents into these classes. We also show that properties of the query result set timeline can help predict the mean average precision of a query. These results show that meta-features associated with a query can be combined with text retrieval techniques to improve our understanding and treatment of text search on documents with timestamps.

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Jones, Rosie, Kumar, Ravi, Pang, Bo and Tomkins, Andrew (2007): "I know what you did last summer": query logs and user privacy. In: Silva, Mario J., Laender, Alberto H. F., Baeza-Yates, Ricardo A., McGuinness, Deborah L., Olstad, Bjørn, Olsen, Øystein Haug and Falcão, André O. (eds.) Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management - CIKM 2007 November 6-10, 2007, Lisbon, Portugal. pp. 909-914. Available online

» 2006 «

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Teevan, Jaime, Adar, Eytan, Jones, Rosie and Potts, Michael (2006): History repeats itself: repeat queries in Yahoo's logs. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2006. pp. 703-704. Available online

Thanks to the ubiquity of the Internet search engine search box, users have come to depend on search engines both to find and re-find information. However, re-finding behavior has not been significantly addressed. Here we look at re-finding queries issued to the Yahoo! search engine by 114 users over a year.

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0003, Bing Liu, Jones, Rosie and Klinkner, Kristina Lisa (2006): Measuring the meaning in time series clustering of text search queries. 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. 836-837. Available online

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Jones, Rosie, Rey, Benjamin, Madani, Omid and Greiner, Wiley (2006): Generating query substitutions. In: Proceedings of the 2006 International Conference on the World Wide Web 2006. pp. 387-396. Available online

We introduce the notion of query substitution, that is, generating a new query to replace a user's original search query. Our technique uses modifications based on typical substitutions web searchers make to their queries. In this way the new query is strongly related to the original query, containing terms closely related to all of the original terms. This contrasts with query expansion through pseudo-relevance feedback, which is costly and can lead to query drift. This also contrasts with query relaxation through boolean or TFIDF retrieval, which reduces the specificity of the query. We define a scale for evaluating query substitution, and show that our method performs well at generating new queries related to the original queries. We build a model for selecting between candidates, by using a number of features relating the query-candidate pair, and by fitting the model to human judgments of relevance of query suggestions. This further improves the quality of the candidates generated. Experiments show that our techniques significantly increase coverage and effectiveness in the setting of sponsored search.

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» 2005 «

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Kumaran, Giridhar, Jones, Rosie and Madani, Omid (2005): Biasing web search results for topic familiarity. In: Herzog, Otthein, Schek, Hans-Jörg and Fuhr, Norbert (eds.) Proceedings of the 2005 ACM CIKM International Conference on Information and Knowledge Management October 31 - November 5, 2005, Bremen, Germany. pp. 271-272. Available online

» 2004 «

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Diaz, Fernando and Jones, Rosie (2004): Using temporal profiles of queries for precision prediction. In: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2004. pp. 18-24. Available online

A key missing component in information retrieval systems is self-diagnostic tests to establish whether the system can provide reasonable results for a given query on a document collection. If we can measure properties of a retrieved set of documents which allow us to predict average precision, we can automate the decision of whether to elicit relevance feedback, or modify the retrieval system in other ways. We use meta-data attached to documents in the form of time stamps to measure the distribution of documents retrieved in response to a query, over the time domain, to create a temporal profile for a query. We define some useful features over this temporal profile. We find that using these temporal features, together with the content of the documents retrieved, we can improve the prediction of average precision for a query.

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» 2003 «

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Jones, Rosie and Fain, Daniel C. (2003): Query word deletion prediction. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2003. pp. 435-436. Available online

Web search query logs contain traces of users' search modifications. One strategy users employ is deleting terms, presumably to obtain greater coverage. It is useful to model and automate term deletion when arbitrary searches are conjunctively matched against a small hand constructed collection, such as a hand-built hierarchy, or collection of high-quality pages matched with key phrases. Queries with no matches can have words deleted till a match is obtained. We provide algorithms which perform substantially better than the baseline in predicting which word should be deleted from a reformulated query, for increasing query coverage in the context of web search on small high-quality collections.

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» 2001 «

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Ghani, Rayid, Jones, Rosie and Mladenic, Dunja (2001): Automatic web search query generation to create minority language corpora. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2001. pp. 432-433. Available online

The Web is a valuable source of language specific resources but collecting, organizing and utilizing this information is difficult. We describe CorpusBuilder, an approach for automatically generating Web-search queries to collect documents in a minority language. It differs from pseudo-relevance feedback in that retrieved documents are labeled by an automatic language classifier as relevant or irrelevant and a subset of documents is used to generate new queries. We experiment with various query-generation methods and query-lengths to find inclusion/exclusion terms that are helpful for finding documents in the target language and find that using odds-ratio scores calculated over the documents acquired so far was one of the most consistently accurate query-generation methods. We also describe experiments using a handful of words elicited from a user instead of initial documents and show that the methods perform similarly. Applying the same approach to multiple languages show that our system generalizes to a variety of languages.

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Ghani, Rayid, Jones, Rosie and Mladenic, Dunja (2001): Mining the Web to Create Minority Language Corpora. In: Proceedings of the 2001 ACM CIKM International Conference on Information and Knowledge Management November 5-10, 2001, Atlanta, Georgia, USA. pp. 279-286. Available online

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Ghani, Rayid, Jones, Rosie and Mladenic, Dunja (2001): Online Learning for Web Query Generation: Finding Documents Matching a Minority Concept on the Web. In: Zhong, Ning, Yao, Yiyu, Liu, Jiming and Ohsuga, Setsuo (eds.) Web Intelligence Research and Development - First Asia-Pacific Conference - WI 2001 October 23-26, 2001, Maebashi City, Japan. pp. 508-513. Available online

» 2000 «

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Ghani, Rayid and Jones, Rosie (2000): Learning a Monolingual Language Model from a Multilingual Text Database. In: Proceedings of the 2000 ACM CIKM International Conference on Information and Knowledge Management November 6-11, 2000, McLean, VA, USA. pp. 187-193. Available online

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Changes to this page (author)

22 Feb 2010: Enabled abstracts to be shown on Rosie Jones's author page.
09 Jul 2009: Author was edited
30 May 2009: Author was edited
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Publication statistics

Publication period:2000-2008
Publication count:16
Number of co-authors:19



Productive colleagues

Rosie Jones's 3 most productive colleagues in number of publications:

Ravi Kumar:27
Andrew Tomkins:23
Xiaofei He:19


Collaboration count

Number of publications with 3 favourite co-authors:

Rayid Ghani:4
Dunja Mladenic:3
Benjamin Rey:2

 

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Learn more about Rosie Jones:
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- ACM
- CSB

Mar 20

Computer programs emerge as the outcome of complex human processes of cognition, communication and negotiation, which serve to establish the meaningful embedding of the computer system in its intended use context.

-- Floyd, 1992, p. 24

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