Conventional document search techniques are constrained by attempting to match individual keywords or phrases to source documents. Thus, these techniques miss out documents that contain semantically similar terms, thereby achieving a relatively low degree of recall. At the same time, processing capabilities and tools for syntactic and semantic analysis of language have advanced to the point whe...

The use of distributional semantics to represent the meaning of a single word has proven to be very effective, but there still is difficulty representing the meaning of larger constituents, such as a noun phrase. In general, it is unclear how to find a representation of phrases that preserves syntactic distinctions and the relationship between a compound’s constituents. This paper is an attempt...

In the effort of building a verb lexicon classifying the most used verbs in Arabic and providing information about their syntax and semantics (Mousser, 2010), the problem of classes over-generation arises because of the overt morphology of Arabic, which codes not only agreement and inflection relations but also semantic information related to thematic arity or other semantic information like ”i...

This paper demonstrates an approach to image retrieval founded on classifying image regions hierarchically based on their semantics (e.g., sky, snow, rocks, etc.) that resemble peoples’ perception rather than on low-level features (e.g., color, texture, shape, etc.). Particularly, we consider to automatically classify regions of outdoor images based on their semantics using the support vector m...

Schema/ontology matching is a critical problem in many application domains, such as, semantic web, schema/ontology integration, data warehouses, e-commerce, catalog matching, etc. Many diverse solutions to the matching problem have been proposed so far. In this paper we present a taxonomy of schema-based matching techniques that builds on the previous work on classifying schema matching approac...

In this paper, we introduce an automatic method for classifying a given question using broad semantic categories in an existing lexical database (i.e., WordNet) as the class tagset. For this, we also constructed a large scale entity supersense database that contains over 1.5 million entities to the 25 WordNet lexicographer’s files (supersenses) from titles of Wikipedia entry. To show the useful...