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- research-articleFebruary 2008
Advertising keyword suggestion based on concept hierarchy
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 251–260https://doi.org/10.1145/1341531.1341564The increasing growth of the World Wide Web constantly enlarges the revenue generated by search engine advertising. Advertisers bid on keywords associated with their products to display their ads on the search result pages. Keyword suggestion methods ...
- research-articleFebruary 2008
A holistic lexicon-based approach to opinion mining
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 231–240https://doi.org/10.1145/1341531.1341561One of the important types of information on the Web is the opinions expressed in the user generated content, e.g., customer reviews of products, forum posts, and blogs. In this paper, we focus on customer reviews of products. In particular, we study ...
- research-articleFebruary 2008
Opinion spam and analysis
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 219–230https://doi.org/10.1145/1341531.1341560Evaluative texts on the Web have become a valuable source of opinions on products, services, events, individuals, etc. Recently, many researchers have studied such opinion sources as product reviews, forum posts, and blogs. However, existing research ...
- research-articleFebruary 2008
Can social bookmarking improve web search?
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 195–206https://doi.org/10.1145/1341531.1341558Social bookmarking is a recent phenomenon which has the potential to give us a great deal of data about pages on the web. One major question is whether that data can be used to augment systems like web search. To answer this question, over the past year ...
- research-articleFebruary 2008
Finding high-quality content in social media
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 183–194https://doi.org/10.1145/1341531.1341557The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content sites based on user contributions --social media sites -- becomes ...
- research-articleFebruary 2008
On ranking controversies in wikipedia: models and evaluation
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 171–182https://doi.org/10.1145/1341531.1341556Wikipedia 1 is a very large and successful Web 2.0 example. As the number of Wikipedia articles and contributors grows at a very fast pace, there are also increasing disputes occurring among the contributors. Disputes often happen in articles with ...
- research-articleFebruary 2008
Understanding temporal aspects in document classification
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 159–170https://doi.org/10.1145/1341531.1341554Due to the increasing amount of information present on the Web, Automatic Document Classification (ADC) has become an important research topic. ADC usually follows a standard supervised learning strategy, where we first build a model using preclassified ...
- research-articleFebruary 2008
Connectivity structure of bipartite graphs via the KNC-plot
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 129–138https://doi.org/10.1145/1341531.1341550In this paper we introduce the k-neighbor connectivity plot, or KNC-plot, as a tool to study the macroscopic connectiv-ity structure of sparse bipartite graphs. Given a bipartite graph G = (U, V, E), we say that two nodes in U are k-neighbors if there ...
- research-articleFebruary 2008
A scalable pattern mining approach to web graph compression with communities
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 95–106https://doi.org/10.1145/1341531.1341547A link server is a system designed to support efficient implementations of graph computations on the web graph. In this work, we present a compression scheme for the web graph specifically designed to accommodate community queries and other random ...
- research-articleFebruary 2008
An experimental comparison of click position-bias models
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 87–94https://doi.org/10.1145/1341531.1341545Search engine click logs provide an invaluable source of relevance information, but this information is biased. A key source of bias is presentation order: the probability of click is influenced by a document's position in the results page. This paper ...
- research-articleFebruary 2008
SoftRank: optimizing non-smooth rank metrics
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 77–86https://doi.org/10.1145/1341531.1341544We address the problem of learning large complex ranking functions. Most IR applications use evaluation metrics that depend only upon the ranks of documents. However, most ranking functions generate document scores, which are sorted to produce a ...
- research-articleFebruary 2008
Fast learning of document ranking functions with the committee perceptron
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 55–64https://doi.org/10.1145/1341531.1341542This paper presents a new variant of the perceptron algorithm using selective committee averaging (or voting). We apply this agorithm to the problem of learning ranking functions for document retrieval, known as the "Learning to Rank" problem. Most ...
- research-articleFebruary 2008
Entropy of search logs: how hard is search? with personalization? with backoff?
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 45–54https://doi.org/10.1145/1341531.1341540How many pages are there on the Web? 5B? 20B? More? Less? Big bets on clusters in the clouds could be wiped out if a small cache of a few million urls could capture much of the value. Language modeling techniques are applied to MSN's search logs to ...
- research-articleFebruary 2008
Beyond basic faceted search
- Ori Ben-Yitzhak,
- Nadav Golbandi,
- Nadav Har'El,
- Ronny Lempel,
- Andreas Neumann,
- Shila Ofek-Koifman,
- Dafna Sheinwald,
- Eugene Shekita,
- Benjamin Sznajder,
- Sivan Yogev
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 33–44https://doi.org/10.1145/1341531.1341539This paper extends traditional faceted search to support richer information discovery tasks over more complex data models. Our first extension adds exible, dynamic business intelligence aggregations to the faceted application, enabling users to gain ...
- research-articleFebruary 2008
Disorder inequality: a combinatorial approach to nearest neighbor search
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 25–32https://doi.org/10.1145/1341531.1341538We say that an algorithm for nearest neighbor search is combinatorial if only direct comparisons between two pairwise similarity values are allowed. Combinatorial algorithms for nearest neighbor search have two important advantages: (1) they do not map ...
- research-articleFebruary 2008
On placing skips optimally in expectation
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 15–24https://doi.org/10.1145/1341531.1341537We study the problem of optimal skip placement in an inverted list. Assuming the query distribution to be known in advance, we formally prove that an optimal skip placement can be computed quite efficiently. Our best algorithm runs in time O (n log n), ...
- research-articleFebruary 2008
Crawl ordering by search impact
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPages 3–14https://doi.org/10.1145/1341531.1341535We study how to prioritize the fetching of new pages under the objective of maximizing the quality of search results. In particular, our objective is to fetch new pages that have the most impact, where the impact of a page is equal to the number of ...
- invited-talkFebruary 2008
Web information management: past, present and future
WSDM '08: Proceedings of the 2008 International Conference on Web Search and Data MiningPage 1https://doi.org/10.1145/1341531.1341532In this talk I will give a brief retrospective on Web Information Management, and will discuss some of the key challenges for the future. I will not give a survey of all work in the area; instead I will give my personal perspective based on work in the ...