TY - JOUR
T1 - Placing search in context
T2 - The concept revisited
AU - Finkelstein, Lev
AU - Gabrilovich, Evgeniy
AU - Matias, Yossi
AU - Rivlin, Ehud
AU - Solan, Zach
AU - Wolfman, Gadi
AU - Ruppin, Eytan
PY - 2002/1
Y1 - 2002/1
N2 - Keyword-based search engines are in widespread use today as a popular means for Web-based information retrieval. Although such systems seem deceptively simple, a considerable amount of skill is required in order to satisfy non-trivial information needs. This paper presents a new conceptual paradigm for performing search in context, that largely automates the search process, providing even non-professional users with highly relevant results. This paradigm is implemented in practice in the IntelliZap system, where search is initiated from a text query marked by the user in a document she views, and is guided by the text surrounding the marked query in that document ("the context"). The context-driven information retrieval process involves semantic keyword extraction and clustering to automatically generate new, augmented queries. The latter are submitted to a host of general and domain-specific search engines. Search results are then semantically reranked, using context. Experimental results testify that using context to guide search, effectively offers even inexperienced users an advanced search tool on the Web.
AB - Keyword-based search engines are in widespread use today as a popular means for Web-based information retrieval. Although such systems seem deceptively simple, a considerable amount of skill is required in order to satisfy non-trivial information needs. This paper presents a new conceptual paradigm for performing search in context, that largely automates the search process, providing even non-professional users with highly relevant results. This paradigm is implemented in practice in the IntelliZap system, where search is initiated from a text query marked by the user in a document she views, and is guided by the text surrounding the marked query in that document ("the context"). The context-driven information retrieval process involves semantic keyword extraction and clustering to automatically generate new, augmented queries. The latter are submitted to a host of general and domain-specific search engines. Search results are then semantically reranked, using context. Experimental results testify that using context to guide search, effectively offers even inexperienced users an advanced search tool on the Web.
KW - Context
KW - Invisible web
KW - Search
KW - Semantic processing
KW - Statistical natural language processing
UR - http://www.scopus.com/inward/record.url?scp=0344029639&partnerID=8YFLogxK
U2 - 10.1145/503104.503110
DO - 10.1145/503104.503110
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AN - SCOPUS:0344029639
SN - 1046-8188
VL - 20
SP - 116
EP - 131
JO - ACM Transactions on Information Systems
JF - ACM Transactions on Information Systems
IS - 1
ER -