We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thesaurus/lexical resource) of structured and semi-structured data sources and the discovery of probabilistic lexical relationships in a data integration environment. ALA performs automatic lexical annotation through the use of probabilistic annotations, i.e. an annotation is associated to a probability value. By performing probabilistic lexical annotation, we discover probabilistic inter-sources lexical relationships among schema elements. ALA extends the lexical annotation module of the MOMIS data integration system. However, it may be applied in general in the context of schema mapping discovery, ontology merging and data integration system and it is pa...
In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined a...
A growing number of resources are available for enriching documents with semantic annotations. While...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
We present ALA, a tool for the automatic lexical annotation (i.e.annotation w.r.t. a thesaurus/lexic...
Abstract: We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thes...
We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thesaurus/lexi...
This paper proposes a method for the automatic discovery of probabilistic relationships in the envir...
Schema matching is the problem of finding relationships among concepts across data sources that are ...
This paper\u2019s aim is to examine what role Lexical Knowledge Extraction plays in data integration...
In this article we present CWSD (Combined Word Sense Disambiguation) a method and a software tool fo...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
We propose a CWSD (Combined Word Sense Disambiguation) algorithm for the automatic annotation of str...
This paper examines extending a database of English verbs, grouped into syntactico-seman...
In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined a...
A growing number of resources are available for enriching documents with semantic annotations. While...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
We present ALA, a tool for the automatic lexical annotation (i.e.annotation w.r.t. a thesaurus/lexic...
Abstract: We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thes...
We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thesaurus/lexi...
This paper proposes a method for the automatic discovery of probabilistic relationships in the envir...
Schema matching is the problem of finding relationships among concepts across data sources that are ...
This paper\u2019s aim is to examine what role Lexical Knowledge Extraction plays in data integration...
In this article we present CWSD (Combined Word Sense Disambiguation) a method and a software tool fo...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
This paper proposes lexical annotation as an effective method to solve the ambiguity problems that a...
We propose a CWSD (Combined Word Sense Disambiguation) algorithm for the automatic annotation of str...
This paper examines extending a database of English verbs, grouped into syntactico-seman...
In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined a...
A growing number of resources are available for enriching documents with semantic annotations. While...
Schema matching is the problem of finding relationships among concepts across heterogeneous data sou...