Traditional Information Retrieval (IR) systems are based on bag-of-words representation. This approach retrieves relevant documents by lexical matching between query and document terms. Due to synonymy and polysemy, lexical methods produce imprecise or incomplete results. In this paper we present how named entities are integrated in SENSE (SEmantic N-levels Search Engine). SENSE is an IR system that tries to overcome the limitations of the ranked keyword approach, by introducing semantic levels which integrate (and not simply replace) the lexical level represented by keywords. Semantic levels provide information about word meanings, as described in a reference dictionary, and named entities. Our aim is to prove that named entities are useful to improve retrieval performance.
Integrating Named Entities in a Semantic Search Engine
CAPUTO, ANNALINA;BASILE, PIERPAOLO;SEMERARO, Giovanni
2010-01-01
Abstract
Traditional Information Retrieval (IR) systems are based on bag-of-words representation. This approach retrieves relevant documents by lexical matching between query and document terms. Due to synonymy and polysemy, lexical methods produce imprecise or incomplete results. In this paper we present how named entities are integrated in SENSE (SEmantic N-levels Search Engine). SENSE is an IR system that tries to overcome the limitations of the ranked keyword approach, by introducing semantic levels which integrate (and not simply replace) the lexical level represented by keywords. Semantic levels provide information about word meanings, as described in a reference dictionary, and named entities. Our aim is to prove that named entities are useful to improve retrieval performance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
