An Augmented User Model for Personalized Search in Collaborative Social Tagging Systems
Citation:
Wenyu Zhao, Dong Zhou, Xuan Wu, Séamus Lawless and Jianxun Liu, An Augmented User Model for Personalized Search in Collaborative Social Tagging Systems, EAI Endorsed Transactions on Collaborative Computing, 3, 12, 2017Download Item:
Abstract:
Alongside the enormous volume of user-generated content posted to World Wide Web, there exists a thriving demand for
search personalization services. To provide personalized services, a user model is usually required. We address the setting
adopted by the majority of previous work, where a user model consists solely of the user’s past information. We construct
an augmented user model from a number of tags and documents. These resources are further processed according to the
user’s past information by exploring external knowledge base. A novel generative model is proposed for user model
generation. This model utilizes recent advances in neural language models such as Word Embeddings with latent semantic
models such as Latent Dirichlet Allocation. We further present a new qu ery expansion method to facilitate the desired
personalized retrieval. Experiments conducted on two real -world collaborative social tagging datasets show that our
proposed methods outperform state-of-the-art methods.
Sponsor
Grant Number
Science Foundation Ireland (SFI)
13/RC/2106
Author's Homepage:
http://people.tcd.ie/selawlesDescription:
PUBLISHED
Author: Lawless, Seamus
Sponsor:
Science Foundation Ireland (SFI)Type of material:
Journal ArticleCollections
Series/Report no:
EAI Endorsed Transactions on Collaborative Computing;3;
12;
Availability:
Full text availableKeywords:
Personalized Social Search, Collaborative Social Tagging Systems, Latent Dirichlet Allocation, Neural Language Model, Query ExpansionSubject (TCD):
Digital Engagement , INFORMATION RETRIEVAL , Personalisation , Personalisation and User-Centric Adaptivity , Personalised Information Retrieval , User ModelingDOI:
10.4108/eai.9-10-2017.154549Metadata
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