Of late, social tagging has become popular trend in information organisation. In context of digital resources the tags assigned by users also play vital role in information retrieval. For information discovery the ‘terms’ used to retrieve the results also depend upon the ‘relevancy’ or ‘weightage’ of the keywords. This study investigates ‘relevancy ranking’ of terms used in the full text of the resource. The common words present in both full text of the article and social tags were considered for the study by employing TF-IDF statistical technique and Jaccard similarity test. The results show that it is possible to assign ‘weight’ to keywords for better results and also determine the significant tags assigned by the user. The Jaccard similarity coefficient test adopted to understand the word similarity between full text words of an article and marine social tags. This work reveals the social tags can enrich metadata for information retrieval.

Management of grid resource information is a challenging and important area considering the potential size of the grid and wide range of resources that should he represented. Though example Grid Information Scrvers exist, hchavior OF these scrvers across different platforms is less well understood.' This paper describes a study we undertook to compare the access language and platform capabilities for three different database platforms, relational, native XML, and LDAP, serving as a grid information server. Our study measures query response times for a range of queries and highlights sensitivities exhibited by the different platforms to variables such as result set size and collections size. 0-7803-8430-W04F$20.00 02004 IEEE

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