Matches in ScholarlyData for { ?s ?p ?o. }
- 406 abstract "We describe Dispute Finder, a browser extension that alerts a user when information they read online is disputed by a source that they might trust. Dispute Finder examines the text on the page that the user is browsing and highlights any phrases that appear to entail claims in its database of known disputed claims. If a user clicks on a highlighted phrase then Dispute Finder will show the user a summary of articles that support other points of view. Dispute Finder builds it's database of disputed claims by crawling web sites that already maintain lists of disputed claims, and by allowing users to enter claims that they believe are disputed. Dispute Finder identifies instances of disputed claims by running a simple textual entailment algorithm inside the browser extension, referring to a cached local copy of a subset of our claim database. Performing these tasks well is a hard problem, and we do not yet claim to have an implementation that is good enough to be compelling for most users. We do however believe that Dispute Finder attacks an interesting problem that, if addressed well, could significantly improve the utility of the web.".
- 406 hasAuthorList authorList.
- 406 isPartOf proceedings.
- 406 keyword "Exploratory search".
- 406 keyword "sensemaking".
- 406 title "Highlighting Disputed Claims on the Web".
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- item-1 hasContent rob-ennals.
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- item-2 hasContent beth-trushkowsky.
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- item-3 hasContent john-mark-agosta.
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- item-4 hasContent tye-rattenbury.
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- item-5 hasContent tad-hirsch.
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- 414 creator andrew-tomkins.
- 414 creator flavio-chierichetti.
- 414 creator ravi-kumar.
- 414 type InProceedings.
- 414 label "Stochastic Models for Tabbed Browsing".
- 414 sameAs 414.
- 414 abstract "We present a model of tabbed browsing that represents a hybrid between a Markov process capturing the graph of web pages, and a branching process capturing the creation, splitting, and dying of tabs. We present a mathematical criterion to characterize whether the process has a steady state independent of initial conditions, and we show how to characterize the limiting behavior in both cases. We perform a series of experiments to compare our tabbed browsing model with pagerank, and show that tabbed browsing is able to explain from 15--25\% of the deviation between actual measured browsing behavior and the behavior predicted by the simple pagerank model. We find this to be a surprising result, as the tabbed browsing model does not make use of any notion of site popularity, but simply captures deviations in user likelihood to open and close tabs from a particular node in the graph.".
- 414 hasAuthorList authorList.
- 414 isPartOf proceedings.
- 414 keyword "Query log".
- 414 keyword "click trail".
- 414 keyword "traffic data mining".
- 414 title "Stochastic Models for Tabbed Browsing".
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- item-1 hasContent flavio-chierichetti.
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- item-2 hasContent ravi-kumar.
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- item-3 hasContent andrew-tomkins.
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- 416 creator andrew-tomkins.
- 416 creator ravi-kumar.
- 416 type InProceedings.
- 416 label "A Characterization of Online Search Behavior".
- 416 sameAs 416.
- 416 abstract "In this paper, we undertake a large-scale study of online user behavior based on search and toolbar logs. We propose a new \emph{CCS taxonomy} of pageviews consisting of Content (news, portals, games, verticals, multimedia), Communication (email, social networking, forums, blogs, chat), and Search (web search, item search, multimedia search). We show that roughly half of all pageviews online are content, $1/3$ are communications, and the remaining $1/6$ are search. We then study the extent to which pages of certain types are revisited by the same user over time, and the mechanisms by which users move from page to page, within and across hosts, and within and across page types. Finally, we characterize behavior within the three primary branches of our taxonomy.".
- 416 hasAuthorList authorList.
- 416 isPartOf proceedings.
- 416 keyword "User models".
- 416 keyword "click logs".
- 416 keyword "personalization".
- 416 keyword "query logs".
- 416 title "A Characterization of Online Search Behavior".
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- item-1 hasContent ravi-kumar.
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- item-2 hasContent andrew-tomkins.
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- 419 creator jian-huang.
- 419 creator jianfeng-gao.
- 419 creator jiangbo-miao.
- 419 creator kuansan-wang.
- 419 creator xiaolong-li.
- 419 type InProceedings.
- 419 label "Exploring Web Scale Language Models for Search Query Processing".
- 419 sameAs 419.
- 419 abstract "It has been widely observed that search queries are composed in a very different style from that of the body or the title of a document. Many techniques explicitly accounting for this language style discrepancy have shown promising results for information retrieval, yet a large scale analysis on the extent of the language differences has been lacking. In this paper, we present an extensive study on this issue by examining the language model properties of search queries and the three text streams associated with each web document: the body, the title, and the anchor text. Our information theoretical analysis shows that queries seem to be composed in a way most similar to how authors summarize documents in anchor texts or titles, offering a quantitative explanation to the observations in previous work. We apply these web scale n-gram language models to three search query processing (SQP) tasks: query spelling correction, query bracketing and long query segmentation. By controlling the size and the order of different language models, we find that the perplexity metric to be a good accuracy indicator for these query processing tasks. We show that using smoothed language models yields significant accuracy gains for query bracketing for instance, compared to using web counts as in the literature. We also demonstrate that applying web-scale language models can have marked accuracy advantage over smaller ones.".
- 419 hasAuthorList authorList.
- 419 isPartOf proceedings.
- 419 keyword "Document representation".
- 419 keyword "corpus".
- 419 keyword "language modeling".
- 419 title "Exploring Web Scale Language Models for Search Query Processing".