Metadataya dayalı ve kişiselleştirilmiş WEB sorgulaması

The advent of the Web has raised new searching and querying problems. Key-word matching based querying techniques that have been widely used by searchengines, return thousands of Web documents for a single query, and most of thesedocuments are generally unrelated to the users? information needs. Towards thegoal of improving the information search needs of Web users, a recent promisingapproach is to index the Web by using metadata and annotations.In this thesis, we model and query Web-based information resources usingmetadata for improved Web searching capabilities. Employing metadata forquerying the Web increases the precision of the query outputs by returning seman-tically more meaningful results. Our Web data model, named ?Web informationspace model?, consists of Web-based information resources (HTML/XML docu-ments on the Web), expert advice repositories (domain-expert-specified metadatafor information resources), and personalized information about users (capturedas user profiles that indicate users? preferences about experts as well as users?knowledge about topics). Expert advice is specified using topics and relationshipsamong topics (i.e., metalinks), along the lines of recently proposed topic mapsstandard. Topics and metalinks constitute metadata that describe the contents ofthe underlying Web information resources. Experts assign scores to topics, met-alinks, and information resources to represent the ?importance? of them. Userprofiles store users? preferences and navigational history information about theinformation resources that the user visits. User preferences, knowledge level ontopics, and history information are used for personalizing the Web search, andimproving the precision of the results returned to the user.We store expert advices and user profiles in an object relational databasemanagement system, and extend the SQL for efficient querying of Web-based in-formation resources through the Web information space model. SQL extensionsinclude the clauses for propagating input importance scores to output tuples, theclause that specifies query stopping condition, and new operators (i.e., text sim-ilarity based selection, text similarity based join, and topic closure). Importancescore propagation and query stopping condition allow ranking of query outputs,and limiting the output size. Text similarity based operators and topic closureoperator support sophisticated querying facilities. We develop a new algebracalled Sideway Value generating Algebra (SVA) to process these SQL extensions.We also propose evaluation algorithms for the text similarity based SVA direc-tional join operator, and report experimental results on the performance of theoperator. We demonstrate experimentally the effectiveness of metadata-basedpersonalized Web search through SQL extensions over the Web information spacemodel against keyword matching based Web search techniques.Keywords: metadata based Web querying, topic maps, user profile, personal-ized Web querying, Sideway Value generating Algebra, score management, textsimilarity based join.