New Methods in Automatic Extracting
Journal of the ACM (JACM)
Pruning long documents for distributed information retrieval
Proceedings of the eleventh international conference on Information and knowledge management
Introduction to the special issue on summarization
Computational Linguistics - Summarization
Predictive caching and prefetching of query results in search engines
WWW '03 Proceedings of the 12th international conference on World Wide Web
ACM Transactions on Information Systems (TOIS)
Fast generation of result snippets in web search
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Design trade-offs for search engine caching
ACM Transactions on the Web (TWEB)
Improved techniques for result caching in web search engines
Proceedings of the 18th international conference on World wide web
Document Compaction for Efficient Query Biased Snippet Generation
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
The automatic creation of literature abstracts
IBM Journal of Research and Development
Mining Query Logs: Turning Search Usage Data into Knowledge
Foundations and Trends in Information Retrieval
On caching search engine query results
Computer Communications
Towards efficient similar sentences extraction
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
The impact of solid state drive on search engine cache management
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Second Chance: A Hybrid Approach for Dynamic Result Caching and Prefetching in Search Engines
ACM Transactions on the Web (TWEB)
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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 the most interesting results. The snippet generation process is very expensive, since it may require to access a number of documents for each issued query. We assert that caching, a popular technique used to enhance performance at various levels of any computing systems, can be very effective in this context. We design and experiment several cache organizations, and we introduce the concept of supersnippet, that is the set of sentences in a document that are more likely to answer future queries. We show that supersnippets can be built by exploiting query logs, and that in our experiments a supersnippet cache answers up to 62% of the requests, remarkably outperforming other caching approaches.