An Online Framework for Supporting the Evaluation of Personalised Information Retrieval Systems

Scope - Personalised Information Retrieval (PIR) has been gaining attention because it investigates intelligent ways for enhancing content delivery. Web users can have personalised services and more accurate information. Problem - Several PIR systems have been proposed in the literature; however, they have not been properly tested or evaluated. Proposal – The authors propose a generally applicable web-based interface, which provides PIR developers and evaluators with: i) implicit recommendations on how to evaluate a specific PIR system; ii) a repository containing studies on user-centred and layered evaluation studies; iii) recommendations on how to best combine different evaluation methods, metrics and measurement criteria in order to most effectively evaluate their system; iv) a UCE methodology which details how to apply existing UCE techniques; v) a taxonomy of evaluations of adaptive systems; and vi) interface translation support (49 languages supported)

DCU-TCD@LogCLEF 2010: re-ranking document collections and query performance estimation

This paper describes the collaborative participation of Dublin City University and Trinity College Dublin in LogCLEF 2010. Two sets of experiments were conducted. First, different aspects of the TEL query logs were analysed after extracting user sessions of consecutive queries on a topic. The relation between the queries and their length (number of terms) and position (first query or further reformulations) was examined in a session with respect to query performance estimators such as query scope, IDF-based measures, simplified query clarity score, and average inverse document collection frequency. Results of this analysis suggest that only some estimator values show a correlation with query length or position in the TEL logs (e.g. similarity score between collection and query). Second, the relation between three attributes was investigated: the user's country (detected from IP address), the query language, and the interface language. The investigation aimed to explore the influence of the three attributes on the user's collection selection. Moreover, the investigation involved assigning different weights to the three attributes in a scoring function that was used to re-rank the collections displayed to the user according to the language and country. The results of the collection re-ranking show a significant improvement in Mean Average Precision (MAP) over the original collection ranking of TEL. The results also indicate that the query language and interface language have more in uence than the user's country on the collections selected by the users

A Survey on Personalized Recommendation Techniques

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Personalized Web Search Using Browsing History and Domain Knowledge Based on Enhanced User Profile

Generic search engines are important for retrieving relevant information from web. However these engines follow the "one size fits all" model which is not adaptable to individual users. Personalized web search is an important field for tuning the traditional IR system for focused information retrieval. This paper is an attempt to improve personalized web search. User's Profile provides an important input for performing personalized web search. This paper proposes a framework for constructing an Enhanced User Profile by using user's browsing history and enriching it using domain knowledge. This Enhanced User Profile can be used for improving the performance of personalized web search. In this paper we have used the Enhanced User Profile specifically for suggesting relevant pages to the user. The experimental results show that the suggestions provided to the user using Enhanced User Profile ae better than those obtained by using a User Profile

Personalised Web Search using Browsing History and Domain Knowledge

Different users have different needs when they submit a query to a web search engine. Personalized web search is able to satisfy individual’s information needs by modeling long-term and short-term user interests based on user past queries, actions and incorporate these in the search process. A Personalized Web Search has various levels of effectiveness for different contexts, queries, users etc. Personalized search has been a most important research area and many techniques have been developed and tested, still many challenges and issues are yet to be explored. This paper proposes a framework for building an Enhanced User Profile by using user's browsing history and improving it using domain knowledge. Enhanced User Profile is used for suggesting relevant web pages to the user. The results of experiments show that the suggestions provided to the user using Enhanced User Profile are better than those obtained by using a User Profile. DOI: 10.17762/ijritcc2321-8169.150315

Provision of Relevant Results on web search Based on Browsing History

Different users submit a query to a web search engine with different needs. The general type of search engines follows the "one size fits all" model which is not flexible to individual users resulting in too many answers for the query.  In order to overcome this drawback, in this paper, we propose a framework for personalized web search which considers individual's interest introducing intelligence into the traditional web search and producing only relevant pages of user interest. This proposed method is simple and efficient which ensures quality suggestions as well as promises for effective and relevant information retrieval. The framework for personalized web search engine is based on user past browsing history. This context is then used to make the web search more personalized. The results are encouraging