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

239
views

120
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

Automatic composition of semantic web services with the abductive event calculus Kırcı, Esra; Çiçekli, Fehime Nihan; Department of Computer Engineering (2008) In today's world, composite web services are widely used in service oriented computing, web mashups and B2B Applications etc. Most of these services are composed manually. However, the complexity of manually composing web services increase exponentially with the increase in the number of available web services, the need for dynamically created/updated/discovered services and the necessity for higher amount of data bindings and type mappings in longer compositions. Therefore, current highly manual web servic...
A hybrid movie recommender using dynamic fuzzy clustering Gürcan, Fatih; Birtürk, Ayşe Nur; Department of Computer Engineering (2010) Recommender systems are information retrieval tools helping users in their information seeking tasks and guiding them in a large space of possible options. Many hybrid recommender systems are proposed so far to overcome shortcomings born of pure content-based (PCB) and pure collaborative fi ltering (PCF) systems. Most studies on recommender systems aim to improve the accuracy and efficiency of predictions. In this thesis, we propose an online hybrid recommender strategy (CBCFdfc) based on content boosted co...
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...
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...

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.