Topic-Centric Querying of Web Information Resourcest

Date

2001-01-01

Author

Altıngövde, İsmail Sengör
Ulusoy, Ö.
Özsoyoğlu, G.
Özsoyoğlu, Z.M.

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

112
views

0
downloads

© Springer-Verlag Berlin Heidelberg 2001.This paper deals with the problem of modeling web information resources using expert knowledge and personalized user information, and querying them in terms of topics and topic relationships. We propose a model for web information resources, and a query language SQL-TC (Topic-Centric SQL) to query the model. The model is composed of web-based information resources (XML or HTML 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 as to which expert advice they would like to follow, and which to ignore, etc). The query language SQL-TC makes use of the metadata information provided in expert advice repositories and embedded in information resources, and employs user preferences to further refine the query output. Query output objects/tuples are ranked with respect to the (expert-judged and user- preference-revised) importance values of requested topics/metalinks, and the query output is limited by either top n-ranked objects/tuples, or objects/tuples with importance values above a given threshold, or both.

Subject Keywords

Information resource, User preference, User profile, Expert advice, Detail level

URI

https://hdl.handle.net/11511/56899

DOI

https://doi.org/10.1007/3-540-44759-8_68

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Topic-centric querying of web information resources Altıngövde, İsmail Sengör; Ulusoy, O; Ozsoyoglu, G; Ozsoyoglu, ZM (2001-01-01) This paper deals with the problem of modeling web information resources using expert knowledge and personalized user information, and querying them in terms of topics and topic relationships. We propose a model for web information resources, and a query language SQL-TC (Topic-Centric SQL) to query the model. The model is composed of web-based information resources (XML or HTML documents on the web), expert advice repositories (domain-expert-specified metadata for information resources), and personalized inf...
Metadata-based modeling of information resources on the web Ozel, SA; Altıngövde, İsmail Sengör; Ulusoy, O; Ozsoyoglu, G; Ozsoyoglu, ZM (Wiley, 2004-01-15) This paper deals with the problem of modeling Web information resources using expert knowledge and personalized user information for improved Web searching capabilities. We propose a "Web information space" model, which is composed of Web-based information resources (HTML/XML [Hypertext Markup Language/Extensible Markup Language] documents on the Web), expert advice repositories (domain-expert-specified meta-data for information resources), and personalized information about users (captured as user profiles...
Publication trends of researchers in Turkey in web of science education and educational research subject field: a descriptive trend analysis Tür, Nurcan; Yıldırım, İbrahim Soner; Department of Computer Education and Instructional Technology (2019) The main aim of this research was to employ bibliometric analysis methods to understand the general trends of peer-reviewed educational articles indexed under the subject areas of “education and educational research” Web of Science bibliometric databases that is the first and well-known bibliometric databases, between 1968 and 2015. This study analyzed a total of 10,729 documents 6,644 of which were articles based on the journal of publication, author institutional affiliation, and co-author collaboration. ...
Text Classification in the Turkish Marketing Domain for Context Sensitive Ad Distribution Engin, Melih; Can, Tolga (2009-09-16) In this paper, we construct and compare several feature extraction approaches in order to find a better solution for classification of Turkish web documents in the marketing domain. We produce our feature extraction techniques using characteristics of the Turkish language, structures of web documents and online content in the marketing domain. We form datasets in different feature spaces and we apply several Support Vector Machine (SVM) configurations on these datasets. We conduct our study considering the ...
Informing the Design of Collaborative Activities in MOOCs using Actionable Predictions Er, Erkan; Gomez-Sanchez, Eduardo; Bote-Lorenzo, Miguel L.; Asensio-Perez, Juan I.; Dimitriadis, Yannis (2019-01-01) With the aim of supporting instructional designers in setting up collaborative learning activities in MOOCs, this paper derives prediction models for student participation in group discussions. The salient feature of these models is that they are built using only data prior to the learning activity, and can thus provide actionable predictions, as opposed to post-hoc approaches common in the MOOC literature. Some learning design scenarios that make use of this actionable information are illustrated.

Citation Formats

İ. S. Altıngövde, Ö. Ulusoy, G. Özsoyoğlu, and Z. M. Özsoyoğlu, “Topic-Centric Querying of Web Information Resourcest,” 2001, vol. 2113, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56899.