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Multi-Agent Web Recommendations [chapter]

Joaquim Neto, A. Jorge Morais
2014 Advances in Intelligent Systems and Computing  
Results show that this multi-agent approach combining different algorithms is capable of improving user's satisfaction.  ...  In previous work we proposed a multi-agent approach using agents with two different algorithms (associative rules and collaborative filtering) and showed the results of the offline tests.  ...  %viewed items that follows a recommendation 23 .76% 50.44% EM The dispersion graph of Figure 2 shows the distributions of item views obtained on online experiments.  ... 
doi:10.1007/978-3-319-07593-8_28 fatcat:mgex4uyjfvhclcn6v5z4z45ooe

Multi-View Data approaches in Recommender Systems: an Overview

Iván Palomares, Sergey V. Kovalchuk
2017 Procedia Computer Science  
Abstract This paper overviews an assortment of recent research work undertaken on recommender system models based on using multiple views of user and item-related data across the recommendation process  ...  Full terms of use are available: Abstract This paper overviews an assortment of recent research work undertaken on recommender system models based on using multiple views of user and item-related data  ...  In [29] they developed a multi-type clustering-based unified recommender framework, that conflates similaritybased user clustering, similarity-based item clustering and trust-based user clustering.  ... 
doi:10.1016/j.procs.2017.11.157 fatcat:gkn5eo4jejd23cvubv6il6ekhq

Applying multi-view based metadata in personalized ranking for recommender systems

Marcos A. Domingues, Camila V. Sundermann, Flávio M. M. Barros, Marcelo G. Manzato, Maria G. C. Pimentel, Solange O. Rezende, Stanley Oliveira
2015 Proceedings of the 30th Annual ACM Symposium on Applied Computing - SAC '15  
In this paper, we propose a multi-view based metadata extraction technique from unstructured textual content in order to be applied in recommendation algorithms based on latent factors.  ...  We evaluate the technique using different recommendation algorithms, and show that better accuracy is obtained when additional information about items is considered.  ...  MULTI-VIEW BASED METADATA Most existing clustering methods usually represent the textual information by using only the terms of the documents, i.e., by using bag-of-words (technical information/ view).  ... 
doi:10.1145/2695664.2695955 dblp:conf/sac/DominguesSBMPR15 fatcat:7zmmx5ujafa75iqnhvxz2uyuuq

A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems

Ali Mamdouh Elkahky, Yang Song, Xiaodong He
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15  
We extend the model to jointly learn from features of items from different domains and user features by introducing a multi-view Deep Learning model.  ...  In this work, we propose a content-based recommendation system to address both the recommendation quality and the system scalability.  ...  Item based collaborative filtering [23] , computes similarity between items based on users who like both items, then recommend the user items similar to the ones she liked before.  ... 
doi:10.1145/2736277.2741667 dblp:conf/www/ElkahkySH15 fatcat:dbvcoir2qngppc2kqdtxk4kuqi

A web usage mining framework for business intelligence

Sonal Tiwari, Deepti Razdan, Prashant Richariya, Shivkumar Tomar
2011 2011 IEEE 3rd International Conference on Communication Software and Networks  
We propose a new framework based on web mining technology. Web mining attempts to determine useful knowledge from secondary data obtained from the interactions of the users with the web.  ...  In this paper, we introduce a web mining solution to business intelligence to discover hidden patterns and business strategies from their customer and web data.  ...  First of all, we propose a new framework based on web mining technology for structure a Web-page recommender system.  ... 
doi:10.1109/iccsn.2011.6014995 fatcat:dblff7j3a5fc3lcjzea5togi2q

Feature Analysis of Recommender Techniques Employed in the Recommendation Engines

Ganapathy
2010 Journal of Computer Science  
Approach: There were a number of recommender systems available to suggest the web pages for the web users.  ...  Problem statement: Recommender Systems (RS) have become a widely researched area as it is extensively used in web usage mining and E-commerce platforms.  ...  , model-based recommendation techniques, multidimensional views of recommendations, multi criteria ratings, nonintrusiveness, flexibility, effectiveness, trustworthiness, scalability and privacy issues  ... 
doi:10.3844/jcssp.2010.748.755 fatcat:eorll36e3rddndb7zkmtvcijp4

M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems [article]

Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-ming Wu
2020 arXiv   pre-print
Particularly, we propose a multi-task multi-view graph representation learning framework (M2GRL) to learn node representations from multi-view graphs for web-scale recommender systems.  ...  Combining graph representation learning with multi-view data (side information) for recommendation is a trend in industry.  ...  One line of research is treating multi-view data (except rating data) as the attributes of items, which are then fed as input of graph-based algorithms.  ... 
arXiv:2005.10110v1 fatcat:2sbn4z6w25cangokcx3uy7d54m

A Hybrid, Multi-dimensional Recommender for Journal Articles in a Scientific Digital Library

Andre Vellino, David Zeber
2007 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops  
[28] describe item-item, user-item, and user-user collaborative filtering in combination with content-based methods both to cluster items and to cluster users.  ...  One approach uses content-based methods for developing user models and clustering users by a content-based similarity measure in order to make collaborative recommendations.  ... 
doi:10.1109/wi-iatw.2007.29 fatcat:cvsml2p3grallbly4w2x4zvijm

A Web Data Mining Framework for E-Commerce Recommender Systems

Jinhua Sun, Yanqi Xie
2009 2009 International Conference on Computational Intelligence and Software Engineering  
In this paper, we introduce a web data mining solution to e-commerce to discover hidden patterns and business strategies from their customer and web data, propose a new framework based on data mining technology  ...  for building a Web-page recommender system, and demonstrate how data mining technology can be effectively applied in an ecommerce environment.  ...  First of all, we propose a new framework based on web data mining technology for building a Web-page recommender system.  ... 
doi:10.1109/cise.2009.5363548 fatcat:cqjuwrjesrgwfh2mkrefexrob4

Effect of Dataset Size on Efficiency of Collaborative Filtering Recommender Systems with Multi-clustering as a Neighbourhood Identification Strategy [chapter]

Urszula Kużelewska
2020 Lecture Notes in Computer Science  
This article presents the results of the experiments validating the advantage of multi-clustering approach, M − CCF , over the traditional methods based on single-scheme clustering.  ...  Determination of accurate neighbourhood of an active user (a user to whom recommendations are generated) is one of the essential problems that collaborative filtering based recommender systems encounter  ...  They are based on either user-based or item-based similarity to make recommendations.  ... 
doi:10.1007/978-3-030-50420-5_25 fatcat:rmlq6f2tijhwlkenhbp7maqogi

A Review on Web Recommendation System

Animesh Shrivastava, Anand Singh Rajawat
2013 International Journal of Computer Applications  
In Web world, there is immense of information available on the internet but user is not capable to find relevant information in short period of time.  ...  In this work, various recommendation systems reviewed to analyze their problems and solutions. In order to improve the recommendation quality, a new web recommendation system is introduced.  ...  Recommendation system suggests items to the web users from the various items available on the web.  ... 
doi:10.5120/14668-2842 fatcat:zweocabzkzdotmjnz7273kh72q

Novel Weighted Hybrid Approach in Recommendation Method

Mr. Avadhut D
2017 International Journal Of Engineering And Computer Science  
Recommendation systems are one of information filtering systems forecasting the items that may be additional interest for user within a big set of items on the basis of user's interests.  ...  This approach uses weighted hybrid recommendation system which combines content based recommendation system and knowledge based recommendation system in order to increase the overall performance of the  ...  Each item is evaluated according to a predefined set of dimensions that provide an aggregated view on the basic item properties.  ... 
doi:10.18535/ijecs/v6i5.36 fatcat:54tpot5cfrhxncrjuy4vhhamju

A multi-agent brokerage platform for media content recommendation

Bruno Veloso, Benedita Malheiro, Juan Carlos Burguillo
2015 International Journal of Applied Mathematics and Computer Science  
It adopts an integrated view of the problem by proposing, on the business-to-business (B2B) side, a brokerage platform to negotiate the media items on behalf of the media content distributors and sources  ...  The filter selection is based on the data available, ranging from the history of items watched to the ratings and/or tags assigned to the items by the viewer.  ...  cloud, which is based on the tags of the users who viewed a particular item; and (iv) the stereotype tag cloud, which is based on the tags attributed to items of a given genre (Rey-López et al., 2010  ... 
doi:10.1515/amcs-2015-0038 fatcat:wbcxrlu6bvc2len6wk4dt2ctle

Accurate and Diverse Recommendations Based on Communities of Interest and Trustable Neighbors

Qihua Liu
2015 International Journal of Security and Its Applications  
In this paper, we integrated a user preference matching algorithm based on communities of interests and a diverse information recommendation algorithm based on trustable neighbors to develop a hybrid information  ...  This paper integrated a user preference matching algorithm based on communities of interests and a diversity information recommendation algorithm based on trustable neighbors to develop a hybrid information  ...  using a hierarchical clustering method based on semantic ontology, and construct multi-hierarchical communities of interest.  ... 
doi:10.14257/ijsia.2015.9.3.07 fatcat:2lt27qgshbfvrc6ymhtjnntwme

A Multi -Perspective Evaluation of MA and GA for Collaborative Filtering Recommender System

Hema Banati, Shikha Mehta
2010 International Journal of Computer Science & Information Technology (IJCSIT)  
one cluster for computing ratings of the unrated items.  ...  Recommender systems are intelligent web applications which generate recommendations keeping in view the user's stated and unstated requirements.  ...  Utility based recommender systems suggest items based on their usefulness for the users.  ... 
doi:10.5121/ijcsit.2010.2508 fatcat:b4dhrivisndbnporde3ouirb7q
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