Browsing by Subject "topic maps"

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Open Access
Implementation of a topic map data model for a Web-based information resource
(2002) Kutlutürk, Mustafa
The Web has become a vast information resource in recent years. Millions of people use the Web on a regular basis and the number is increasing rapidly. The Web is the largest center in the world presenting almost all of the social, economical, educational, etc. activities and anyone from all over the word can visit this huge place even though he does not have to stand up from his sit. Due to its hugeness, finding desired data on the Web in a timely and cost effective way is a problem of wide interest. In the last several years, many search engines have been created to help Web users find desired information. However, most of these search engines employ topic-independent search methods that rely heavily on keyword-based approaches where the users are presented with a lot of unnecessary search results. In this thesis, we present a data model using topic maps standards for Webbased information resources. In this model, topics, topic associations and topic occurrences (called as topic metalinks and topic sources in this study) are the fundamental concepts. In fact, the presented model is a metadata model that describes the content of the Web-based information resource and creates virtual knowledge maps over the modeled information resource. Thus, semantic indexing of the Web-based information resource is performed for allowing efficient search and querying the data on the resource. iv Additionally, we employ full text indexing in the presented model by using a widely accepted method that is inverted file index. Due to the rapid increase of data, the dynamic update of the inverted file index during the addition of new documents is inevitable. We have implemented an efficient dynamic update scheme in the presented model for the employed inverted file index method. The presented topic map data model provides combining the powers of both keyword-based search and topic-centric search methods. We also provide a prototype search engine verifying that our presented model contributes very much to the problem of efficient and effective search and querying of the Web-based information resources.
Open Access
Metadata-based and personalized web querying
(2004) Özel, Selma Ayşe
The advent of the Web has raised new searching and querying problems. Keyword matching based querying techniques that have been widely used by search engines, return thousands of Web documents for a single query, and most of these documents are generally unrelated to the users’ information needs. Towards the goal of improving the information search needs of Web users, a recent promising approach is to index the Web by using metadata and annotations. In this thesis, we model and query Web-based information resources using metadata for improved Web searching capabilities. Employing metadata for querying the Web increases the precision of the query outputs by returning semantically more meaningful results. Our Web data model, named “Web information space model”, consists of Web-based information resources (HTML/XML documents on the Web), expert advice repositories (domain-expert-specified metadata for information resources), and personalized information about users (captured as user profiles that indicate users’ preferences about experts as well as users’ knowledge about topics). Expert advice is specified using topics and relationships among topics (i.e., metalinks), along the lines of recently proposed topic maps standard. Topics and metalinks constitute metadata that describe the contents of the underlying Web information resources. Experts assign scores to topics, metalinks, and information resources to represent the “importance” of them. User profiles store users’ preferences and navigational history information about the information resources that the user visits. User preferences, knowledge level on topics, and history information are used for personalizing the Web search, and improving the precision of the results returned to the user. We store expert advices and user profiles in an object relational database iv v management system, and extend the SQL for efficient querying of Web-based information resources through the Web information space model. SQL extensions include the clauses for propagating input importance scores to output tuples, the clause that specifies query stopping condition, and new operators (i.e., text similarity based selection, text similarity based join, and topic closure). Importance score propagation and query stopping condition allow ranking of query outputs, and limiting the output size. Text similarity based operators and topic closure operator support sophisticated querying facilities. We develop a new algebra called Sideway Value generating Algebra (SVA) to process these SQL extensions. We also propose evaluation algorithms for the text similarity based SVA directional join operator, and report experimental results on the performance of the operator. We demonstrate experimentally the effectiveness of metadata-based personalized Web search through SQL extensions over the Web information space model against keyword matching based Web search techniques.