Automatic generation of probabilistic relationships for improving schema matching

Po, Laura; Sorrentino, Serena

doi:10.1016/j.is.2010.09.004

Cited by 27 publications

(26 citation statements)

References 32 publications

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“…If such a transcoding is not available a semi-automatic technique should be adopted (Po & Sorrentino, 2011); • Owner rating: Source owners themselves often rate their data in terms of completeness, correctness, and freshness;…”

Section: Quality Assessmentmentioning

confidence: 99%

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Abelló

Darmont

Etcheverry

et al. 2013

International Journal of Data Warehousing and Mining

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Section: Quality Assessmentmentioning

confidence: 99%

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Abelló

Darmont

Etcheverry

et al. 2013

International Journal of Data Warehousing and Mining

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“…To understand which of the synsets better express the meaning of a keyword in a plot we may adopt Word Sense Disambiguation techniques [21]. The semantic relationships between synsets can be used for enhancing the keyword meaning by adding all its hypernyms and hyponyms [22,26].…”

Section: Discussionmentioning

confidence: 99%

A Non-intrusive Movie Recommendation System

Farinella¹,

Bergamaschi

2012

On the Move to Meaningful Internet Systems: OTM 2012

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Abstract. Several recommendation systems have been developed to support the user in choosing an interesting movie from multimedia repositories. The widely utilized collaborative-filtering systems focus on the analysis of user profiles or user ratings of the items. However, these systems decrease their performance at the start-up phase and due to privacy issues, when a user hides most of his personal data. On the other hand, content-based recommendation systems compare movie features to suggest similar multimedia contents; these systems are based on less invasive observations, however they find some difficulties to supply tailored suggestions. In this paper, we propose a plot-based recommendation system, which is based upon an evaluation of similarity among the plot of a video that was watched by the user and a large amount of plots that is stored in a movie database. Since it is independent from the number of user ratings, it is able to propose famous and beloved movies as well as old or unheard movies/programs that are still strongly related to the content of the video the user has watched. We experimented different methodologies to compare natural language descriptions of movies (plots) and evaluated the Latent Semantic Analysis (LSA) to be the superior one in supporting the selection of similar plots. In order to increase the efficiency of LSA, different models have been experimented and in the end, a recommendation system that is able to compare about two hundred thousands movie plots in less than a minute has been developed.

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“…These techniques aim to associate meanings to terms labels, by matching the text strings labels with elements belonging to reference ontologies / knowledge base thesauri(see [20] for a survey). Among the existing approaches, in [26] Description Logics techniques are exploited for checking the proximities and consistencies of the meanings associated to the keywords in a query through ontologies; in [21] a probabilistic framework supports the selections of possible meanings associated to schema labels. Identifying the meaning of terms composing a keyword query separately is in general insufficient for understanding the intended meaning of a keyword query; context information can be very useful.…”

Section: Issues To Addressmentioning

confidence: 99%

Keyword Search over Relational Databases: Issues, Approaches and Open Challenges

Bergamaschi

Guerra

Simonini

2014

Lecture Notes in Computer Science

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Abstract. In this paper, we overview the main research approaches developed in the area of Keyword Search over Relational Databases. In particular, we model the process for solving keyword queries in three phases: the management of the user's input, the search algorithms, the results returned to the user. For each phase we analyze the main problems, the solutions adopted by the most important system developed by researchers and the open challenges. Finally, we introduce two open issues related to multi-source scenarios and database sources handling instance not fully accessible.

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Automatic generation of probabilistic relationships for improving schema matching

Cited by 27 publications

References 32 publications

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A Non-intrusive Movie Recommendation System

Keyword Search over Relational Databases: Issues, Approaches and Open Challenges

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