A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Combining document representations for known-item search
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Simple BM25 extension to multiple weighted fields
Proceedings of the thirteenth ACM international conference on Information and knowledge management
A generative theory of relevance
A generative theory of relevance
Linear feature-based models for information retrieval
Information Retrieval
Matching resumes and jobs based on relevance models
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A Probabilistic Retrieval Model for Semistructured Data
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Refining Keyword Queries for XML Retrieval by Combining Content and Structure
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Extracting structured information from user queries with semi-supervised conditional random fields
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Retrieval experiments using pseudo-desktop collections
Proceedings of the 18th ACM conference on Information and knowledge management
Learning concept importance using a weighted dependence model
Proceedings of the third ACM international conference on Web search and data mining
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
A test collection for entity search in DBpedia
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Many search applications involve documents with structure or fields. Since query terms often are related to specific structural components, mapping queries to fields and assigning weights to those fields is critical for retrieval effectiveness. Although several field-based retrieval models have been developed, there has not been a formal justification of field weighting. In this work, we aim to improve the field weighting for structured document retrieval. We first introduce the notion of field relevance as the generalization of field weights, and discuss how it can be estimated using relevant documents, which effectively implements relevance feedback for field weighting. We then propose a framework for estimating field relevance based on the combination of several sources. Evaluation on several structured document collections show that field weighting based on the suggested framework improves retrieval effectiveness significantly.