Effective site finding using link anchor information
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
WWW '03 Proceedings of the 12th international conference on World Wide Web
Query expansion using associated queries
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Mining anchor text for query refinement
Proceedings of the 13th international conference on World Wide Web
Challenges in enterprise search
ADC '04 Proceedings of the 15th Australasian database conference - Volume 27
Towards the next generation of enterprise search technology
IBM Systems Journal
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Using annotations in enterprise search
Proceedings of the 15th international conference on World Wide Web
Mining search engine query logs for query recommendation
Proceedings of the 15th international conference on World Wide Web
Getting work done on the web: supporting transactional queries
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Navigating the intranet with high precision
Proceedings of the 16th international conference on World Wide Web
Optimizing query rewrites for keyword-based advertising
Proceedings of the 9th ACM conference on Electronic commerce
Towards rich query interpretation: walking back and forth for mining query templates
Proceedings of the 19th international conference on World wide web
Understanding queries in a search database system
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Improving recommendation for long-tail queries via templates
Proceedings of the 20th international conference on World wide web
Rewrite rules for search database systems
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
Suggestion set utility maximization using session logs
Proceedings of the 20th ACM international conference on Information and knowledge management
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Enterprise search — the new frontier?
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Gumshoe quality toolkit: administering programmable search
Proceedings of the 21st ACM international conference on Information and knowledge management
Next generation data analytics at IBM research
Proceedings of the VLDB Endowment
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Enterprise search is challenging for several reasons, notably the dynamic terminology and jargon that are specific to the enterprise domain. This challenge is partly addressed by having domain experts maintaining the enterprise search engine and adapting it to the domain specifics. Those administrators commonly address user complaints about relevant documents missing from the top matches. For that, it has been proposed to allow administrators to influence search results by crafting query-rewrite rules, each specifying how queries of a certain pattern should be modified or augmented with additional queries. Upon a complaint, the administrator seeks a semantically coherent rule that is capable of pushing the desired documents up to the top matches. However, the creation and maintenance of rewrite rules is highly tedious and time consuming. Our goal in this work is to ease the burden on search administrators by automatically suggesting rewrite rules. This automation entails several challenges. One major challenge is to select, among many options, rules that are ``natural'' from a semantic perspective (e.g., corresponding to closely related and syntactically complete concepts). Towards that, we study a machine-learning classification approach. The second challenge is to accommodate the cross-query effect of rules---a rule introduced in the context of one query can eliminate the desired results for other queries and the desired effects of other rules. We present a formalization of this challenge as a generic computational problem. As we show that this problem is highly intractable in terms of complexity theory, we present heuristic approaches and optimization thereof. In an experimental study within IBM intranet search, those heuristics achieve near-optimal quality and well scale to large data sets.