Ranking Web Services using Centralities and Social Indicators Tilo Zemke author José Ignacio Fernández-Villamor author Carlos A Iglesias author 2012 text </titleInfo> <originInfo> <issuance>continuing</issuance> <publisher>SciTePress</publisher> <place> <placeTerm type="text">Wrocław, PL</placeTerm> </place> </originInfo> <genre authority="marcgt">periodical</genre> <genre>academic journal</genre> </relatedItem> <abstract>Nowadays, developers of web application mashups face a sheer overwhelming variety and pluralism of web services. Therefore, choosing appropriate web services to achieve specific goals requires a certain amount of knowledge as well as expertise. In order to support users in choosing appropriate web services it is not only important to match their search criteria to a dataset of possible choices but also to rank the results according to their relevance, thus minimizing the time it takes for taking such a choice. Therefore, we investigated six ranking approaches in an empirical manner and compared them to each other. Moreover, we have had a look on how one can combine those ranking algorithms linearly in order to maximize the quality of their outputs.</abstract> <subject> <topic>Mashup; Web Service Composition; Ranking</topic> </subject> <identifier type="citekey">Tilo12</identifier> <part> <date>2012</date> </part> </mods> </modsCollection>