Luo Si

Milad Shokouhi

Web search has significantly evolved in recent years. For many years, web search engines such as Google and Yahoo! were only providing search service over text documents. Aggregated search was one of the first steps to go beyond text search, and was the beginning of a new era for information seeking and retrieval. These days, web search engines support aggregated search over a number of verticals, and blend different types of documents (e.g. images, videos) in their search results. Moreover, web search engines have started to crawl and search the hidden web. Federated search (federated information retrieval or distributed information retrieval) has played a key role in providing the technology for aggregated search and crawling the hidden web. The application of federated search is not limited to the web search engines. There are many scenarios such as digital libraries in which information is distributed across different sources/servers. Peer-to-peer networks and personalized search are two examples in which federated search has been successfully used for searching multiple independent collections. Federated Search provides a comprehensive summary of the research done to date, looks at some of the challenges still to be faced, and suggests some directions for future research on this important and current topic.

Federated Search

Maarten de Rijke

Krisztian Balog

Yi Fang

Pavel Serdyukov

People have looked for experts since before the advent of computers. With advances in information retrieval technology, coupled with the large-scale availability of traces of knowledge-related activities, computer systems that can fully automate the process of locating expertise have become a reality. The past decade has witnessed tremendous interest and a wealth of results in expertise retrieval as an emerging subdiscipline in information retrieval. This survey highlights advances in models and algorithms relevant to this field. We draw connections among methods proposed in the literature and summarize them in five groups of basic approaches. These serve as the building blocks for more advanced models that arise when we consider a range of content-based factors that may impact the strength of association between a topic and a person. We also discuss practical aspects of building an expert search system and present applications of the technology in other domains such as blog distillation and entity retrieval. The limitations of current approaches are also pointed out. We end our survey with a set of conjectures on what the future may hold for expertise retrieval research.

Luo Si

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