Using ontology based web usage mining and object clustering for recommendation

Download

index.pdf

Date

2010

Author

Yılmaz, Hakan

Metadata

Show full item record

Item Usage Stats

36
views

18
downloads

Many e-commerce web sites such as online book retailers or specialized information hubs such as online movie databases make use of recommendation systems where users are directed to items of interests based on past user interactions. Keyword-based approaches, collaborative and content filtering techniques have been tried and used over the years each having their own shortcomings. While keyword based approaches are naive and do not take content or context into account collaborative and content filtering techniques suffer from biased ratings, first item and first-rater problems. Recent approaches try to incorporate underlying semantic properties of data by employing ontology based usage mining. This thesis aims to design a recommendation system based on ontological data where web pages are seen as objects with attributes and relations. Instead of relying on users’ content ratings, user sessions are clustered on a iv semantic level to capture different behavioral groups. Since semantic information is used for the clustering distance function, each cluster represents a behavior group instead of simpler data groups. New users are then assigned to individual clusters that best represent their behavior and recommendations are generated accordingly. In this thesis we use the recommendation results as a means for measuring the effectiveness of the clusters we have generated. We have compared the results obtained using the ontological data and the results obtained without using it and shown that semantic integrating semantic knowledge increases both precision and recall.

Subject Keywords

Computer enginnering., Ontology.

URI

http://etd.lib.metu.edu.tr/upload/12611902/index.pdf
https://hdl.handle.net/11511/19679

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Mining frequent semantic event patterns Söztutar, Enis; Toroslu, İsmail Hakkı; Department of Computer Engineering (2009) Especially with the wide use of dynamic page generation, and richer user interaction in Web, traditional web usage mining methods, which are based on the pageview concept are of limited usability. For overcoming the difficulty of capturing usage behaviour, we define the concept of semantic events. Conceptually, events are higher level actions of a user in a web site, that are technically independent of pageviews. Events are modelled as objects in the domain of the web site, with associated properties. A sam...
A recommendation system combining context-awarenes and user profiling in mobile environment Ulucan, Serkan; Erkmen, Aydan Müşerref; Department of Electrical and Electronics Engineering (2005) Up to now various recommendation systems have been proposed for web based applications such as e-commerce and information retrieval where a large amount of product or information is available. Basically, the task of the recommendation systems in those applications, for example the e-commerce, is to find and recommend the most relevant items to users/customers. In this domain, the most prominent approaches are أcollaborative filteringؤ and أcontent-based filteringؤ. Sometimes these approaches are called as أ...
A content boosted collaborative filtering approach for movie recommendation based on local & global similarity and missing data prediction Özbal, Gözde; Alpaslan, Ferda Nur; Department of Computer Engineering (2009) Recently, it has become more and more difficult for the existing web based systems to locate or retrieve any kind of relevant information, due to the rapid growth of the World Wide Web (WWW) in terms of the information space and the amount of the users in that space. However, in today's world, many systems and approaches make it possible for the users to be guided by the recommendations that they provide about new items such as articles, news, books, music, and movies. However, a lot of traditional recommen...
Abductive planning approach for automated web service composition using only user specified inputs and outputs Kuban, Esat Kaan; Çiçekli, Fehime Nihan; Department of Computer Engineering (2009) In recent years, web services have become an emerging technology for communication and integration between applications in many areas such as business to business (B2B) or business to commerce (B2C). In this growing technology, it is hard to compose web services manually because of the increasing number and compexity of web services. Therefore, automation of this composition process has gained a considerable amount of popularity. Automated web service composition can be achieved either by generating the com...
Un/cefact ccts based e-business document design and customization environment for achivieng data interoperability Tunçer, Fulya; Doğaç, Asuman; Department of Computer Engineering (2009) The leading effort for creating a standard semantic basis for business documents to solve the electronic business document interoperability problem came from the UN/CEFACT (United Nations Centre for Trade Facilitation and Electronic Business) Core Components Technical Specification (CCTS) through a conceptual document modeling methodology. Currently, the main challenge in using UN/CEFACT CCTS based approaches is that the document artifacts are stored in spreadsheets and this makes it very difficult to disco...

Citation Formats

H. Yılmaz, “Using ontology based web usage mining and object clustering for recommendation,” M.S. - Master of Science, Middle East Technical University, 2010.