[1]
Gumshoe quality toolkit: administering programmable search
Information retrieval demonstration session
/
Bao, Zhuowei
/
Kimelfeld, Benny
/
Li, Yunyao
/
Raghavan, Sriram
/
Yang, Huahai
Proceedings of the 2012 ACM Conference on Information and Knowledge
Management
2012-10-29
p.2716-2718
© Copyright 2012 ACM
Summary: Enterprise search is challenging due to various reasons, notably the dynamic
terminology and domain structure that are specific to the enterprise, combined
with the fact that search deployments are typically managed by domain experts
who are not necessarily search experts. To address that, it has been proposed
to design search architectures that feature two principles: comprehensibility
of the ranking mechanism and customizability of the search engine by means of
intuitive runtime rules. The proposed demonstration operates on top of an
engine implementation based on this search philosophy, and provides an
administrator toolkit to realize the two principles. In particular, the toolkit
provides a complete visualization of the provenance (hence ranking) of search
results, embeds an editor for programming runtime rules, facilitates the
investigation of (the cause of) missing or low-ranked desired results, and
provides suggestions of rewrite rules to handle such results.
[2]
Automatic suggestion of query-rewrite rules for enterprise search
Query completion and correction
/
Bao, Zhuowei
/
Kimelfeld, Benny
/
Li, Yunyao
Proceedings of the 35th Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2012-08-12
p.591-600
© Copyright 2012 ACM
Summary: 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.
[3]
EDITED BOOK
Search Computing: Broadening Web Search
Lecture Notes in Computer Science 7538
/
Ceri, Stefano
/
Brambilla, Marco
2012
n.16
p.254
Springer Berlin Heidelberg
DOI: 10.1007/978-3-642-34213-4
== Extraction and Integration ==
Web Data Reconciliation: Models and Experiences (1-15)
+ Blanco, Lorenzo
+ Crescenzi, Valter
+ Merialdo, Paolo
+ Papotti, Paolo
A Domain Independent Framework for Extracting Linked Semantic Data from Tables (16-33)
+ Mulwad, Varish
+ Finin, Tim
+ Joshi, Anupam
Knowledge Extraction from Structured Sources (34-52)
+ Unbehauen, Jörg
+ Hellmann, Sebastian
+ Auer, Sören
+ Stadler, Claus
Extracting Information from Google Fusion Tables (53-67)
+ Brambilla, Marco
+ Ceri, Stefano
+ Cinefra, Nicola
+ Sarma, Anish Das
+ Forghieri, Fabio
+ et al
Materialization of Web Data Sources (68-81)
+ Bozzon, Alessandro
+ Ceri, Stefano
+ Zagorac, Srdan
== Query and Visualization Paradigms ==
Natural Language Interfaces to Data Services (82-97)
+ Guerrisi, Vincenzo
+ Torre, Pietro La
+ Quarteroni, Silvia
Mobile Multi-domain Search over Structured Web Data (98-110)
+ Aral, Atakan
+ Akin, Ilker Zafer
+ Brambilla, Marco
Clustering and Labeling of Multi-dimensional Mixed Structured Data (111-126)
+ Brambilla, Marco
+ Zanoni, Massimiliano
Visualizing Search Results: Engineering Visual Patterns Development for the Web (127-142)
+ Morales-Chaparro, Rober
+ Preciado, Juan Carlos
+ Sánchez-Figueroa, Fernando
== Exploring Linked Data ==
Extending SPARQL Algebra to Support Efficient Evaluation of Top-K SPARQL Queries (143-156)
+ Bozzon, Alessandro
+ Valle, Emanuele Della
+ Magliacane, Sara
Thematic Clustering and Exploration of Linked Data (157-175)
+ Castano, Silvana
+ Ferrara, Alfio
+ Montanelli, Stefano
Support for Reusable Explorations of Linked Data in the Semantic Web (176-190)
+ Cohen, Marcelo
+ Schwabe, Daniel
== Games, Social Search and Economics ==
A Survey on Proximity Measures for Social Networks (191-206)
+ Cohen, Sara
+ Kimelfeld, Benny
+ Koutrika, Georgia
Extending Search to Crowds: A Model-Driven Approach (207-222)
+ Bozzon, Alessandro
+ Brambilla, Marco
+ Ceri, Stefano
+ Mauri, Andrea
BetterRelations: Collecting Association Strengths for Linked Data Triples with a Game (223-239)
+ Hees, Jörn
+ Roth-Berghofer, Thomas
+ Biedert, Ralf
+ Adrian, Benjamin
+ Dengel, Andreas
An Incentive-Compatible Revenue-Sharing Mechanism for the Economic Sustainability of Multi-domain Search Based on Advertising (240-254)
+ Brambilla, Marco
+ Ceppi, Sofia
+ Gatti, Nicola
+ Gerding, Enrico H.
