Proceedings ArticleDOI
Improving web search ranking by incorporating user behavior information
Eugene Agichtein,Eric D. Brill,Susan T. Dumais +2 more
- Vol. 52, Iss: 2, pp 19-26
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TLDR
In this paper, the authors show that incorporating implicit feedback can augment other features, improving the accuracy of a competitive web search ranking algorithm by as much as 31% relative to the original performance.Abstract:
We show that incorporating user behavior data can significantly improve ordering of top results in real web search setting. We examine alternatives for incorporating feedback into the ranking process and explore the contributions of user feedback compared to other common web search features. We report results of a large scale evaluation over 3,000 queries and 12 million user interactions with a popular web search engine. We show that incorporating implicit feedback can augment other features, improving the accuracy of a competitive web search ranking algorithms by as much as 31% relative to the original performance.read more
Citations
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Book
Learning to Rank for Information Retrieval
TL;DR: Three major approaches to learning to rank are introduced, i.e., the pointwise, pairwise, and listwise approaches, the relationship between the loss functions used in these approaches and the widely-used IR evaluation measures are analyzed, and the performance of these approaches on the LETOR benchmark datasets is evaluated.
Journal ArticleDOI
Filter Bubbles, Echo Chambers, and Online News Consumption
TL;DR: For instance, this paper found that social networks and search engines are associated with an increase in the mean ideological distance between individuals, and that the magnitude of the effects is relatively modest, while also finding that the vast majority of online news consumption is accounted for by individuals simply visiting the home pages of their favorite, typically mainstream, news outlets.
Proceedings ArticleDOI
Predicting clicks: estimating the click-through rate for new ads
TL;DR: This work shows that it can be used to use features of ads, terms, and advertisers to learn a model that accurately predicts the click-though rate for new ads, and shows that using this model improves the convergence and performance of an advertising system.
Proceedings ArticleDOI
Novelty and diversity in information retrieval evaluation
Charles L. A. Clarke,Maheedhar Kolla,Gordon V. Cormack,Olga Vechtomova,Azin Ashkan,Stefan Büttcher,Ian MacKinnon +6 more
TL;DR: This paper develops a framework for evaluation that systematically rewards novelty and diversity into a specific evaluation measure, based on cumulative gain, and demonstrates the feasibility of this approach using a test collection based on the TREC question answering track.
Journal ArticleDOI
Exploratory Search:Beyond the Query-Response Paradigm
Ryen W. White,Resa A. Roth +1 more
TL;DR: This lecture introduces exploratory search, relates it to relevant extant research, outline the features of exploratorySearch systems, discuss the evaluation of these systems, and suggest some future directions for supporting exploratorysearch.
References
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Journal ArticleDOI
The anatomy of a large-scale hypertextual Web search engine
Sergey Brin,Lawrence Page +1 more
TL;DR: This paper provides an in-depth description of Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and looks at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.
Journal Article
The Anatomy of a Large-Scale Hypertextual Web Search Engine.
Sergey Brin,Lawrence Page +1 more
TL;DR: Google as discussed by the authors is a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems.
Book
Introduction to Modern Information Retrieval
Gerard Salton,Michael J. McGill +1 more
TL;DR: Reading is a need and a hobby at once and this condition is the on that will make you feel that you must read.
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Modern Information Retrieval
TL;DR: In this article, the authors present a rigorous and complete textbook for a first course on information retrieval from the computer science (as opposed to a user-centred) perspective, which provides an up-to-date student oriented treatment of the subject.
Proceedings ArticleDOI
Optimizing search engines using clickthrough data
TL;DR: The goal of this paper is to develop a method that utilizes clickthrough data for training, namely the query-log of the search engine in connection with the log of links the users clicked on in the presented ranking.