Crowdsourcing for Top-K Query Processing over Uncertain Data
نویسندگان
چکیده
منابع مشابه
Humans Fighting Uncertainty: Crowdsourcing for Top-K Query Processing
Querying uncertain data has become a prominent application due to the proliferation of user-generated content from social media and of data streams from sensors. When data ambiguity cannot be reduced algorithmically, crowdsourcing proves a viable approach, which consists in posting tasks to humans and harnessing their judgment for improving the confidence about data values or relationships. Thi...
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An uncertain or probabilistic database is defined as a probability distribution over a set of deterministic database instances called possible worlds. In the classical deterministic setting, the query processing problem is to compute the set of tuples representing the answer of a given query on a given database. In the probabilistic setting, this problem becomes the computation of all pairs (t,...
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Query processing over uncertain data is very important in many applications due to the existence of uncertainty in real-world data. In this paper, we propose a novel and important query for uncertain data, namely probabilistic top-(k, l) range (PTR) query, which retrieves l uncertain tuples that are expected to meet score range constraint [s1, s2] and have the maximum top-k probabilities but no...
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Ranking techniques have been widely used in ubiquitous applications like recommendation, information retrieval, etc. For ranking computation hostile but human friendly items, crowdsourcing is considered as an emerging technique to process the ranking by human power. However, there is a lack of an easy-to-use toolkit for answering crowdsourced top-k query with minimal effort. In this work, we de...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2016
ISSN: 1041-4347
DOI: 10.1109/tkde.2015.2462357