Metadata-based and personalized web querying
| buir.advisor | Ulusoy, Özgür | |
| dc.contributor.author | Özel, Selma Ayşe | |
| dc.date.accessioned | 2016-07-01T10:59:45Z | |
| dc.date.available | 2016-07-01T10:59:45Z | |
| dc.date.issued | 2004 | |
| dc.description | Cataloged from PDF version of article. | en_US |
| dc.description.abstract | 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. | en_US |
| dc.description.provenance | Made available in DSpace on 2016-07-01T10:59:45Z (GMT). No. of bitstreams: 1 0002474.pdf: 655904 bytes, checksum: ef914a56a0c3d892cd53c58976eb4241 (MD5) Previous issue date: 2004 | en |
| dc.description.statementofresponsibility | Özel, Selma Ayşe | en_US |
| dc.format.extent | xvi, 137 leaves | en_US |
| dc.identifier.itemid | BILKUTUPB080118 | |
| dc.identifier.uri | http://hdl.handle.net/11693/29443 | |
| dc.language.iso | English | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | metadata based Web querying | en_US |
| dc.subject | text similarity based join | en_US |
| dc.subject | score management | en_US |
| dc.subject | Sideway Value generating Algebra | en_US |
| dc.subject | personalized Web querying | en_US |
| dc.subject | user profile | en_US |
| dc.subject | topic maps | en_US |
| dc.subject.lcc | QA76.9.D3 O94 2004 | en_US |
| dc.subject.lcsh | Database management. | en_US |
| dc.title | Metadata-based and personalized web querying | en_US |
| dc.type | Thesis | en_US |
| thesis.degree.discipline | Computer Engineering | |
| thesis.degree.grantor | Bilkent University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Ph.D. (Doctor of Philosophy) |
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