The multimedia information retrieval community has dedicated extensive research effort to the problem of content-based image retrieval (CBIR). However, these systems find their main limitation in the difficulty of creating pictorial queries. As a result,...

Short URLs have become ubiquitous. Especially popular within social networking services, short URLs have seen a significant increase in their usage over the past years, mostly due to Twitter's restriction of message length to 140 characters. In this ...

There is a widespread intuitive sense that different kinds of information spread differently on-line, but it has been difficult to evaluate this question quantitatively since it requires a setting where many different kinds of information spread in a ...

We analyze the information credibility of news propagated through Twitter, a popular microblogging service. Previous research has shown that most of the messages posted on Twitter are truthful, but the service is also used to spread misinformation and ...

Bucket testing, also known as A/B testing, is a practice that is widely used by on-line sites with large audiences: in a simple version of the methodology, one evaluates a new feature on the site by exposing it to a very small fraction of the total user ...

The clustering coefficient of a node in a social network is a fundamental measure that quantifies how tightly-knit the community is around the node. Its computation can be reduced to counting the number of triangles incident on the particular node in ...

We continue the line of research on graph compression started with WebGraph, but we move our focus to the compression of social networks in a proper sense (e.g., LiveJournal): the approaches that have been used for a long time to compress web graphs ...

K-Nearest Neighbor Graph (K-NNG) construction is an important operation with many web related applications, including collaborative filtering, similarity search, and many others in data mining and machine learning. Existing methods for K-NNG ...

Many real-life graphs such as social networks and peer-to-peer networks capture the relationships among the nodes by using trust scores to label the edges. Important usage of such networks includes trust prediction, finding the most reliable or trusted ...

Targeting interest to match a user with services (e.g. news, products, games, advertisements) and predicting friendship to build connections among users are two fundamental tasks for social network systems. In this paper, we show that the information ...

A social rating network (SRN) is a social network in which edges represent social relationships and users (nodes) express ratings on some of the given items. Such networks play an increasingly important role in reviewing websites such as Epinions.com or ...

Understanding a network's temporal evolution appears to require multiple observations of the graph over time. These often expensive repeated crawls are only able to answer questions about what happened from observation to observation, and not what ...

Recently answers for fact lookup queries have appeared on major search engines. For example, for the query Barack Obama date of birth Google directly shows "4 August 1961" above its regular results. In this paper, we describe FACTO, an end-to-end system ...

We introduce the problem of evaluating graph constraints in content-based publish/subscribe (pub/sub) systems. This problem formulation extends traditional content-based pub/sub systems in the following manner: publishers and subscribers are connected ...

Modern search engines are expected to make documents searchable shortly after they appear on the ever changing Web. To satisfy this requirement, the Web is frequently crawled. Due to the sheer size of their indexes, search engines distribute the crawled ...

Search engines today offer a rich user experience, no longer restricted to "ten blue links". For example, the query "Canon EOS Digital Camera" returns a photo of the digital camera, and a list of suitable merchants and prices. Similar results are ...

In this paper, we present a highly scalable algorithm for structurally clustering webpages for extraction. We show that, using only the URLs of the webpages and simple content features, it is possible to cluster webpages effectively and efficiently. At ...

In this paper, we study the problem of expanding a set of given seed entities into a more complete set by discovering other entities that also belong to the same concept set. A typical example is to use "Canon" and "Nikon" as seed entities, and derive ...

We provide a novel method of evaluating search results, which allows us to combine existing editorial judgments with the relevance estimates generated by click-based user browsing models. There are evaluation methods in the literature that use clicks ...

The explosion of Web opinion data has made essential the need for automatic tools to analyze and understand people's sentiments toward different topics. In most sentiment analysis applications, the sentiment lexicon plays a central role. However, it is ...