3,315 research outputs found
First International Workshop on User Interfaces for Crowdsourcing and Human Computation
No full textRecent years witnessed an explosion in the number and variety of data crowdsourcing initiatives. From OpenStreetMap to Amazon Mechanical Turk, developers and practitioners have been striving to create user interfaces able to effectively and efficiently support the creation, exploration, and analysis of crowdsourced information. The extensive usage of crowdsourcing techniques brings a major change of paradigm with respect to traditional user interface for data collection and exploration, as effectiveness, speed, and interaction quality concerns play a central role in supporting very demanding incentives, including monetary ones. The First International Workshop on User Interfaces for Crowdsourcing and Human Computation (CrowdUI 2014), co-located with the AVI 2014 conference, brought together researchers and practitioners from a wide range of areas interested in discussing the user interaction challenges posed by crowdsourcing systems. © 2014 ACM
Model-Driven Development of Audio-Visual Web Search Applications: The PHAROS Demonstration
No full textBuild your complex search: social, behavioral, and micro-economic perspective on modern Web search
No full textSo far, Web search has been a playground for few giants.
However, while traditional search engines are superb in their
ability of extracting the Web pages that most closely match with
user’s keywords, they fail in going beyond such simple paradigm.
On the other side, an increasing number of data sets is becoming
available on the Web as (semi) structured data instead of userconsumable
pages. Web search has huge potentials for
improvement thanks to the high quality of these data sources, but
this can be achieved only by designing new search applications
that federate those sources. To tackle the long tail of user
requirements and tastes, the need arises for new ways of thinking
and designing search applications: application providers (and
perhaps even end users) will need to build their own, customized
search experiences, by combining search services available on the
Web at the purpose of solving specific search needs. Individual
and collective social experience will be more and more
influencing search results. In our work we investigate the social,
economic, and behavioral trends that push towards a completely
different interpretation of the search task on the Web. We discuss
how the technology and the micro-economic models must change
to face these challenges
Towards a Top-K SPARQL Query Benchmark Generator
No full textThe research on optimization of top-k SPARQL query would largely benefit from the establishment of a benchmark that allows comparing different approaches. For such a benchmark to be meaningful, at least two requirements should hold: 1) the benchmark should resemble reality as much as possible, and 2) it should stress the features of the topk SPARQL queries both from a syntactic and performance perspective. In this paper we propose Top-k DBPSB: an extension of the DBpedia SPARQL benchmark (DBPSB), a benchmark known to resemble reality, with the capabilities required to compare SPARQL engines on top-k queries
Second International Workshop on DATA Visualization and Integration on the Web (DATAVIEW'11)
No full textWelcome to the 2nd International Workshop on DATA Visualization and Integration
on the Web (DATAVIEW'11), held in conjunction with the European Conference on Web
Services (ECOWS'11), September 14-16, 2011 in Lugano, Switzerland
Search upon UML repositories with text matching techniques
No full textAs the quantity of software artifacts, mainly source code and software models, stored in repositories increases, the need for their efficient search becomes more important. In this paper we propose content-based query (a.k.a query-by-example) approach for searching software model repositories, in order to retrieve significant models or model fragments. The query-by-example search conveys the user need in form of a model or pattern specified in a coarse way. Our approach incorporates analysis and indexing of models using textual information retrieval techniques, which exploit the knowledge of the metamodel the models conform to. This allows us to explore different segmentation granularities on models and different indexing techniques ranging from simple bag of words, to index structures which integrate metamodel information. We detail the proposed theoretical framework, the implementation of the method upon open-source architectures, and we discuss the results of our experiments upon a public dataset of UML models
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