Using Folksonomies and Similarity Matching
نویسندگان
چکیده
Libraries, private and public, offer valuable resources to library patrons. As of today the only way to locate information archived exclusively in libraries is through their catalogs. Library patrons, however, often find it difficult to formulate a proper query, which requires using specific keywords assigned to different fields of desired library catalog records, to obtain relevant results. These improperly formulated queries often yield irrelevant results or no results at all. This negative experience in dealing with existing library systems turn library patrons away from querying library catalogs directly; instead, they rely on Web search engines to perform their searches first and upon obtaining the initial information (such as titles, subject headings, or authors) on the desired library materials, they query library catalogs. This searching strategy is an evidence of failure of today‟s library systems. In solving this problem, we propose an enhanced library system, which allows partial, similarity matching of (i) tags defined by ordinary users at a folksonomy site that describe the content of books and (ii) unrestricted keywords specified by an ordinary library patron in Corresponding Author 2 a query to search for relevant library catalog records. The proposed library system allows patrons posting a query Q using commonly-used words and ranks the retrieved results according to their degrees of resemblance with Q while maintaining the query processing time comparable with the one achieved by current library search engines.
منابع مشابه
Evaluation of Similarity Measures for Template Matching
Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...
متن کاملInstanced-Based Mapping between Thesauri and Folksonomies
The emergence of web based systems in which users can annotate items, raises the question of the semantic interoperability between vocabularies originating from collaborative annotation processes, often called folksonomies, and keywords assigned in a more traditional way. If collections are annotated according to two systems, e.g. with tags and keywords, the annotated data can be used for insta...
متن کاملHarnessing the power of folksonomies for formal ontology matching on-the-fly
This paper is a short introduction to our work on building and using folksonomies to facilitate communication between Semantic Web agents with disparate ontological representations. We brie y present the Semantic Matcher, a system that measures the semantic proximity between terms in interacting agents' ontologies at run-time, fully automatically and minimally: that is, only for semantic mismat...
متن کاملA procedure for Web Service Selection Using WS-Policy Semantic Matching
In general, Policy-based approaches play an important role in the management of web services, for instance, in the choice of semantic web service and quality of services (QoS) in particular. The present research work illustrates a procedure for the web service selection among functionality similar web services based on WS-Policy semantic matching. In this study, the procedure of WS-Policy publi...
متن کاملMeasures of semantic similarity in folksonomies Group : d 618
Folksonomies are new, user driven classification structures and an important part of Web 2.0. Folksonomies are the only one approach that can keep up with todays web expansion rate, by utilizing users as classificators of web's content. Folksonomies, when containing sufficient amount of data, can be exploited in several ways. This particular work concentrates on measures of semantic similarity ...
متن کاملMatching of Polygon Objects by Optimizing Geometric Criteria
Despite the semantic criteria, geometric criteria have different performances on polygon feature matching in different vector datasets. By using these criteria for measuring the similarity of two polygons in all matchings, the same results would not have been obtained. To achieve the best matching results, the determination of optimal geometric criteria for each dataset is considered necessary....
متن کامل