By Nicola Ferro
The study domain names of data retrieval and databases have ordinarily followed diverse methods to details administration. even though, lately, there was an expanding cross-fertilization one of the fields and now many study demanding situations are transversal to them. With this in brain, a wintry weather tuition used to be prepared in Bressanone, Italy, in February 2013, in the context of the EU-funded examine undertaking PROMISE (Participative examine Laboratory for Multimedia and Multilingual details platforms Evaluation). PROMISE geared toward advancing the experimental overview of advanced multimedia and multilingual details structures in an effort to help members, advertisement entities and groups, who layout, strengthen, hire and enhance such complicated structures. the general aim of PROMISE used to be to carry a unified surroundings gathering information, wisdom, instruments and methodologies and to aid the person group inquisitive about experimental overview. This ebook constitutes the result of the PROMISE iciness institution 2013 and includes nine invited lectures from the examine domain names of knowledge retrieval and databases plus brief papers of the simplest pupil poster awards. a wide number of themes are coated, together with databases, info retrieval, experimental assessment, metrics and statistics, semantic seek, key-phrase seek in databases, semi-structured seek, review either in details retrieval and databases, crowdsourcing and social media.
Read Online or Download Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures PDF
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Extra info for Bridging Between Information Retrieval and Databases: PROMISE Winter School 2013, Bressanone, Italy, February 4-8, 2013. Revised Tutorial Lectures
44 K. Bontcheva, V. Tablan, and H. Cunningham Fig. 5. The Broccoli Interactive Query Building UI Figure 6 shows a query where the user has typed the word “ontology”, which in GATE can refer to various concepts in the GATE domain ontology of Java classes and their documentation. Due to this ambiguity, the results are ﬁrst a list of candidate concepts. Once the user selects the intended GATE concept, a list of matching documents is displayed, listed by type (Java code, forum post, etc). Their titles are clickable, which then shows the document content with the query terms highlighted (see the example Java code in the bottom right corner of Figure 6).
Temporal proximity involves merging documents that were created close-in-time. Semantical proximity involves joining text with the same approximate content. Proximity based on the authorship implies concatenating documents produced by the same author. These operations, however, are not obvious and they are applications dependent. For example, it is relatively easy to concatenate documents of the same author if we want to proﬁle and retrieve these documents based on their authors, like it is done for documents in traditional collections.
M´ımir is highly scalable. 150 million web pages were indexed successfully, using two hundred Amazon EC2 Large Instances running for a week to produce a federated index . net , building M´ımir semantic indexes on the Amazon cloud is straightforward. 42 K. Bontcheva, V. Tablan, and H. Cunningham 6 User Friendly Semantic Search Interfaces SPARQL-like semantic searches that tapping into ontological knowledge and LOD resources are extremely powerful. However, writing formal SPARQL queries is beyond the ability of the vast majority of users.