Abstract. Current web search engines return query-biased snippets for each document they list in a result set. For efficiency, search engines operating on large collections need to cache snippets for common queries, and to cache documents to allow fast generation of snippets for uncached queries

Web Search Engines ’ result pages contain references to the top-k documents relevant for the query submitted by a user. Each document is represented by a title, a snippet and a URL. Snippets, i.e. short sentences showing the portions of the document being relevant to the query, help users to select

Web Search Engines ’ result pages contain references to the top-k documents relevant for the query submitted by a user. Each document is represented by a title, a snippet and a URL. Snippets, i.e. short sentences showing the portions of the document being relevant to the query, help users to select

-search on generating result snippets for XML search remains untouched. In this paper we present a system, eXtract, which ad-dresses this important yet open problem. We identify that a good XML result snippet should be a self-contained mean-ingful information unit of a small size that effectively sum-marizes this query

to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext) previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each

Aiming to improve user experience for a job search engine, in this paper we propose an idea to switch from query-biased snippets used by most web search engines to rich structured snippets associated with the main sections of a job posting page, which are more appropriate for job search due

The presentation of query biased document snippets as part of results pages presented by search engines has become an expectation of search engine users. In this paper we explore the algorithms and data structures required as part of a search engine to allow efficient generation of query biased

The presentation of query biased document snippets as part of results pages presented by search engines has become an expectation of search engine users. In this paper we explore the algorithms and data structures required as part of a search engine to allow efficient generation of query biased

information triggers a negative selection decision. We use a special document genre, archival finding aids, where results have a complex document structure and currently available systems experiment with structured summaries having both by an archivist) and query-biased snippets (showing the matching keywords

Content on the Internet is always changing. We explore the value of biasing search result snippets towards new webpage content. We present results from a user study comparing traditional queryfocused snippets with snippets that emphasize new page content for two query types: general and trending