scholarly journals A Context-Awareness Modeling User Profile Construction Method for Personalized Information Retrieval System

2014 ◽  
Vol 14 (2) ◽  
pp. 122-129 ◽  
Author(s):  
Jee Hyun Kim ◽  
Qian Gao ◽  
Young Im Cho
Keyword(s):  
Information Retrieval ◽  
Context Awareness ◽  
Retrieval System ◽  
User Profile ◽  
Construction Method ◽  
Information Retrieval System

Personalization Information Retrieval Based on Unigram Language Model

2013 ◽  
Vol 321-324 ◽  
pp. 2269-2273
Author(s):  
Yang Xin Yu
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Language Model ◽  
User Profile ◽  
Information Retrieval System ◽  
Model Framework ◽  
Feedback Model ◽  
Multiple Domain ◽  
Query Model

Personalization information retrieval is very useful in information retrieval system, the user profile can be used to represent the favorites or interests of user. Many methods to personalization have been studied in extending query with user profile. A proposed navel method which use the context of long-term user profile with multiple domain to extend query model under the unigram language model framework, uses the new query model to retrieve and get more interesting results for users. Combined with psudo relevance feedback model, the proposed method get better performance. Experimental results show that the proposed method in this paper is effective.

Personalization Information Retrieval Based on Topic Directory

2013 ◽  
Vol 712-715 ◽  
pp. 2659-2663
Author(s):  
Yang Xin Yu ◽  
Yi Zhou Zhang
Keyword(s):  
Information Retrieval ◽  
Semantic Similarity ◽  
Retrieval System ◽  
User Profile ◽  
Information Retrieval System ◽  
Tree Structure ◽  
Experimental Results ◽  
User Profiles ◽  
User Interests ◽  
Computing Process

Personalization information retrieval is very useful in information retrieval system, the user profile can be used to represent the favorites or interests of user. This paper introduces how to automatically learn user interests, build user profiles and re-rank search results.A topic directory method is proposed to calculate the semantic similarity, which takes multi-inheritance into consideration, and then optimize the computing process based on the tree structure of inheritance relationship. Experiments are conducted to compare our method with the popular directory based search methods (e.g., Google Directory Search). Experimental results show that the proposed method in this paper can effectively capture personalization and improve the accuracy of personalized search over existing approaches.

Sign in / Sign up

Export Citation Format

Share Document