The 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 ...

One 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 ...

Evaluative 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 ...

Social 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 ...

The 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 ...

Wikipedia 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 ...

Due 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 ...

Personal names are an important kind of Web queries in Web search, and yet they are special in many ways. Strategies for retrieving information on personal names should therefore be different from the strategies for other types of queries. To improve ...

Organizing Web search results into hierarchical categories facilitates users' browsing through Web search results, especially for ambiguous queries where the potential results are mixed together. Previous methods on search result classification are ...

In 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 ...

Online communities in the form of message boards, listservs, and newsgroups continue to represent a considerable amount of the social activity on the Internet. Every year thousands of groups ourish while others decline into relative obscurity; likewise, ...

A formal type of scientific and academic collaboration is coauthorship which can be represented by a coauthorship network. Coauthorship networks are among some of the largest social networks and offer us the opportunity to study the mechanisms ...

A 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 ...

Search 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 ...

We 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 ...

We analyze the traffic-weighted Web host graph obtained from a large sample of real Web users over about seven months. A number of interesting structural properties are revealed by this complex dynamic network, some in line with the well-studied boolean ...

This 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 ...

How 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 ...

This 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 ...

We 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 ...