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This paper presents P3Q, a fully decentralized gossip-based protocol to personalize query processing in social tagging systems. P3Q dynamically associates each user with social acquaintances sharing similar tagging behaviours. Queries are gossiped among such acquaintances, computed on the fly in a collaborative, yet partitioned manner, and results are(More)
Caches of results are critical components of modern Web search engines, since they enable lower response time to frequent queries and reduce the load to the search engine backend. Results in long-lived cache entries may become stale, however, as search engines continuously update their index to incorporate changes to the Web. Consequently, it is important(More)
This article presents P4Q, a fully decentralized gossip-based protocol to personalize query processing in social tagging systems. P4Q dynamically associates each user with social acquaintances sharing similar tagging behaviors. Queries are gossiped among such acquaintances, computed on-the-fly in a collaborative, yet partitioned manner, and results are(More)
A multi-site web search engine is composed of a number of search sites geographically distributed around the world. Each search site is typically responsible for crawling and indexing the web pages that are in its geographical neighborhood. A query is selectively processed on a subset of search sites that are predicted to return the best-matching results.(More)
Traditionally, the efficiency and effectiveness of search systems have both been of great interest to the information retrieval community. However, an in-depth analysis on the interplay between the response latency of web search systems and users' search experience has been missing so far. In order to fill this gap, we conduct two separate studies aiming to(More)
Several social networking applications enable users to view the events generated by other users, typically friends in the social network, in the form of ``news feeds''. Friends and events are typically maintained per user and cached in memory to enable efficient generation of news feeds. Caching user friends and events, however, raises concerns about the(More)
We present the first personalized peer-to-peer top-<i>k</i> search protocol for a collaborative tagging system. Each peer maintains relevant personalized information about its tagging behavior as well as that of its social neighbors, and uses those to locally process its queries. Extensive experiments based on a real-world dataset crawled from del.icio.us(More)
Understanding the impact of a search system's response latency on its users' searching behaviour has been recently an active research topic in the information retrieval and human-computer interaction areas. Along the same line, this paper focuses on the user impact of search latency and makes the following two contributions. First, through a controlled(More)
Matching entities from different information sources is a very important problem in data analysis and data integration. It is, however, challenging due to the number and diversity of information sources involved, and the significant editorial efforts required to collect sufficient training data. In this paper, we present an approach that leverages user(More)