Structural proximity searching for large collections of semi-structured data
Proceedings of the tenth international conference on Information and knowledge management
ACM SIGIR Forum
XRANK: ranked keyword search over XML documents
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A Metric for Distributions with Applications to Image Databases
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Automatic categorization of query results
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Efficient keyword search for smallest LCAs in XML databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Keyword Proximity Search in XML Trees
IEEE Transactions on Knowledge and Data Engineering
Ordering the attributes of query results
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Multiway SLCA-based keyword search in XML data
Proceedings of the 16th international conference on World Wide Web
Identifying meaningful return information for XML keyword search
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Addressing diverse user preferences in SQL-query-result navigation
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
XSEarch: a semantic search engine for XML
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Effective keyword search for valuable lcas over xml documents
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Query biased snippet generation in XML search
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Reasoning and identifying relevant matches for XML keyword search
Proceedings of the VLDB Endowment
Retrieving meaningful relaxed tightest fragments for XML keyword search
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Standing Out in a Crowd: Selecting Attributes for Maximum Visibility
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Effective XML Keyword Search with Relevance Oriented Ranking
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Structured search result differentiation
Proceedings of the VLDB Endowment
Facetedpedia: dynamic generation of query-dependent faceted interfaces for wikipedia
Proceedings of the 19th international conference on World wide web
Improving XML search by generating and utilizing informative result snippets
ACM Transactions on Database Systems (TODS)
FACeTOR: cost-driven exploration of faceted query results
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Exploiting and Maintaining Materialized Views for XML Keyword Queries
ACM Transactions on Internet Technology (TOIT)
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Studies show that about 50% of Web search is for information exploration purposes, where a user would like to investigate, compare, evaluate, and synthesize multiple relevant results. Due to the absence of general tools that can effectively analyze and differentiate multiple results, a user has to manually read and comprehend potential large results in an exploratory search. Such a process is time consuming, labor intensive and error prone. Interestingly, we find that the metadata information embedded in structured data provides a potential for automating or semi-automating the comparison of multiple results. In this article we present an approach for structured data search result differentiation. We define the differentiability of query results and quantify the degree of difference. Then we define the problem of identifying a limited number of valid features in a result that can maximally differentiate this result from the others, which is proved NP-hard. We propose two local optimality conditions, namely single-swap and multi-swap, and design efficient algorithms to achieve local optimality. We then present a feature type-based approach, which further improves the quality of the features identified for result differentiation. To show the usefulness of our approach, we implemented a system CompareIt, which can be used to compare structured search results as well as any objects. Our empirical evaluation verifies the effectiveness and efficiency of the proposed approach.