Semantic Information Retrieval on Medical Texts

Medical Texts Classification Based on Keywords Using Semantic Information

This paper presents a method to classify medical texts based on keywords with the support of additional semantic information. The classification is performed in two phases. In the first phase, keyword sets are extracted for each type of disease presented in the training set.

Information retrieval on Turkish texts

We study information retrieval (IR) on Turkish texts using a large-scale test collection that contains 408,305 documents and 72 ad hoc queries. We examine the effects of several stemming options and query-document matching functions on retrieval performance. We show that a simple word truncation approach, a word truncation approach that uses language dependent corpus statistics, and an elaborat...

Proximity of Terms, Texts and Semantic Vectors in Information Retrieval

Information Retrieval from Annotated Texts

Methods for the correct and eecient handling of annotations in a full-text retrieval system are investigated. The problem with annotations is that they cannot be treated as regular text, since this would disrupt proximity searches, but on the other hand, they cannot be ignored, as they may carry important information. Moreover, in some cases, a user may wish to restrict a search to prespeciied ...

Semantic relations in concept-based cross-language medical information retrieval

We explore and evaluate the usefulness of semantic annotation, particularly semantic relations, in cross-language information retrieval in the medical domain. As the baseline for automatic semantic annotation we use UMLS, which specifies semantic relations between medical concepts. We developed two methods to improve the accuracy and yield of relations in CLIR: a method for relation filtering a...