Paper Info
Title
Extending search to crowds: a model-driven approach
Abstract
In many settings, the human opinion provided by an expert or knowledgeable user can be more useful than factual information retrieved by a search engine. Search systems do not capture the subjective opinions and recommendations of friends, or fresh, online-provided information that require contextual or domain-specific expertise. Search results obtained from conventional search engines can be complemented by crowdsearch, an online interaction with crowds, selected among friends, experts, or people who are presently at a given location; an interplay between conventional and search-based queries can occur, so that the two search methods can support each other. In this paper, we use a model-driven approach for specifying and implementing a crowdsearch application; in particular we define two models: the "Query Task Model", representing the meta-model of the query that is submitted to the crowd and the associated answers; and the "User Interaction Model", showing how the user can interact with the query model to fulfil her needs. Our solution allows for a top-down design approach, from the crowd-search task design, down to the crowd answering system design. Our approach also grants automatic code generation, thus leading to quick prototyping of crowd-search applications.
Year
DOI
Venue
2012
10.1007/978-3-642-34213-4_14
SeCO Book
Keywords
Field
DocType
top-down design approach,query task model,extending search,model-driven approach,crowd-search task design,search system,crowd answering system design,search engine,search method,conventional search engine,search result
Crowds,Web search query,World Wide Web,Search engine,Job design,Computer science,Web query classification,Systems design,Code generation,Exploratory search
Conference
Citations 
PageRank 
References 
2
0.44
23
Authors
4
Name
Order
Citations
PageRank
Alessandro Bozzon164171.27
Marco Brambilla21152119.40
Stefano Ceri367721657.41
Andrea Mauri410916.75