Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

Interpersonal relations and nurses' job satisfaction through knowledge and usage of relational skills

Background/rationale: Many interpersonal labor disputes stem from the lack of communication skills and the relational problems in the interactions between health professionals. Aims/methods: A qualitative study was conducted in a Spanish hospital in order to get to know how the communicative interaction between hospital nurses is like in relation to the nurses' interpersonal interaction and communication skills developed in their working relationships. Twenty-one hospital nurses between 29 and 55 years old, working in different wards, were interviewed. Open-ended interview discourses were transcribed verbatim and analyzed using qualitative content analysis. Results: The following four key themes were analyzed: communication and sender; communication and awareness of who has the problem; non-verbal communication; communication and recipient. Conclusion: The results of this study highlight the need to broaden nurses' relational–communication skills in order to increase job satisfaction.