Approximate Matching in ACSM Dissimilarity Measure

Adaptive Approximate Record Matching

Typographical data entry errors and incomplete documents, produce imperfect records in real world databases. These errors generate distinct records which belong to the same entity. The aim of Approximate Record Matching is to find multiple records which belong to an entity. In this paper, an algorithm for Approximate Record Matching is proposed that can be adapted automatically with input error...

adaptive approximate record matching

typographical data entry errors and incomplete documents, produce imperfect records in real world databases. these errors generate distinct records which belong to the same entity. the aim of approximate record matching is to find multiple records which belong to an entity. in this paper, an algorithm for approximate record matching is proposed that can be adapted automatically with input error...

Approximate Query Answering exploiting a Dissimilarity Measure based on Local Models

We present a context-based method, founded in the instance-based learning and the disjunctive version space approach, for performing approximate query answering of knowledge bases expressed in Description Logics. Differently from the current approaches, it is able to supply answers, even though they are not logically entailed by the knowledge base (e.g. there are inconsistent assertions). Moreo...

Approximate Measures of Semantic Dissimilarity under Uncertainty

We propose semantic distance measures based on the criterion of approximate discernibility and on evidence combination. In the presence of incomplete knowledge, the distance measures the degree of belief in the discernibility of two individuals by combining estimates of basic probability masses related to a set of discriminating features. We also suggest ways to extend this distance for compari...

Approximate Matching in XML