NDLI: Review expert collaborative recommendation algorithm based on topic relationship

Content Provider	IEEE Xplore Digital Library
Author	Shengxiang Gao Zhengtao Yu Linbin Shi Xin Yan Haixia Song
Copyright Year	2014
Abstract	The project review information plays an important role in the recommendation of review experts. In this paper, we aim to determine review expert's rating by using the historical rating records and the final decision results on the previous projects, and by means of some rules, we construct a rating matrix for projects and experts. For the data sparseness problem of the rating matrix and the "cold start" problem of new expert recommendation, we assume that those projects/experts with similar topics have similar feature vectors and propose a review expert collaborative recommendation algorithm based on topic relationship. Firstly, we obtain topics of projects/experts based on latent Dirichlet allocation (LDA) model, and build the topic relationship network of projects/experts. Then, through the topic relationship between projects/experts, we find a neighbor collection which shares the largest similarity with target project/expert, and integrate the collection into the collaborative filtering recommendation algorithm based on matrix factorization. Finally, by learning the rating matrix to get feature vectors of the projects and experts, we can predict the ratings that a target project will give candidate review experts, and thus achieve the review expert recommendation. Experiments on real data set show that the proposed method could predict the review expert rating more effectively, and improve the recommendation effect of review experts.
Starting Page	403
Ending Page	411
Page Count	9
File Size	1777483
File Format	PDF
ISSN	23299266
Volume Number	2
Issue Number	4
Language	English
Publisher Date	2015-10-10
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Chinese Association of Automation
Subject Keyword	Collaboration Prediction algorithms Gaussian distribution Sparse matrices Marine vehicles Data models Analytical models matrix factorization Review expert recommendation topic relationship collaborative filtering
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Artificial Intelligence Control and Systems Engineering Information Systems

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

SBMF: Similarity-Based Matrix Factorization for Collaborative Recommendation

Extreme Learning Machine combining matrix factorization for collaborative filtering

Hybrid collaborative filtering model for improved recommendation

Using Category and Keyword for Personalized Recommendation: A Scalable Collaborative Filtering Algorithm

An improved collaborative filtering algorithm combining content-based algorithm and user activity

An Optimization Method for Recommendation System Based on User Implicit Behavior

Binomial Matrix Factorization for Discrete Collaborative Filtering

Collaborative filtering by PSO-based MMMF

Generalized Probabilistic Matrix Factorizations for Collaborative Filtering

Review expert collaborative recommendation algorithm based on topic relationship

Similar Documents

SBMF: Similarity-Based Matrix Factorization for Collaborative Recommendation

Extreme Learning Machine combining matrix factorization for collaborative filtering

Hybrid collaborative filtering model for improved recommendation

Using Category and Keyword for Personalized Recommendation: A Scalable Collaborative Filtering Algorithm

An improved collaborative filtering algorithm combining content-based algorithm and user activity

An Optimization Method for Recommendation System Based on User Implicit Behavior

Binomial Matrix Factorization for Discrete Collaborative Filtering

Collaborative filtering by PSO-based MMMF

Generalized Probabilistic Matrix Factorizations for Collaborative Filtering

Review expert collaborative recommendation algorithm based on topic relationship