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Hybrid critiquing-based recommender systems

Li Chen, Pearl Pu
2007 Proceedings of the 12th international conference on Intelligent user interfaces - IUI '07  
We propose a novel critiquing-based recommender interface, the hybrid critiquing interface that integrates the user self-motivated critiquing facility to compensate for the limitations of system-proposed  ...  In addition, users expressed higher subjective opinions of the hybrid critiquing interface than the interface simply providing system-proposed critiques, and they would more likely return to it for future  ...  critiquing-based recommender system.  ... 
doi:10.1145/1216295.1216308 dblp:conf/iui/ChenP07 fatcat:4zyyvgnaanecpnbcs5iolqbaby

The evaluation of a hybrid critiquing system with preference-based recommendations organization

Li Chen, Pearl Pu
2007 Proceedings of the 2007 ACM conference on Recommender systems - RecSys '07  
The critiquing-based recommender system mainly aims to guide users to make an accurate and confident decision, while requiring them to consume a low level of effort.  ...  By means of real user evaluation, we proved that a new hybrid critiquing system design that integrates the preferencebased recommendations organization technique for critiques suggestion can effectively  ...  To converge the strengths from both the critiquing approaches, we have proposed to combine them into a hybrid critiquing-based recommender system [3] , and found that this kind of hybrid system could  ... 
doi:10.1145/1297231.1297263 dblp:conf/recsys/ChenP07 fatcat:pp2msyuiqretphoqixd3uh2qhe

Critiquing-based recommenders: survey and emerging trends

Li Chen, Pearl Pu
2011 User modeling and user-adapted interaction  
Critiquing-based recommender systems elicit users' feedback, called critiques, which they made on the recommended items.  ...  With the help of categorization analysis, the survey reveals three principal branches of critiquing based recommender systems, using respectively natural language based, system-suggested, and user-initiated  ...  The so called hybrid critiquing-based recommender system was hence proposed, and it is believed that in such system, people The product being critiqued System-suggested compound critiques User-initiated  ... 
doi:10.1007/s11257-011-9108-6 fatcat:4t25wlfbxbgexa3drwesbz6pz4

Interaction design guidelines on critiquing-based recommender systems

Li Chen, Pearl Pu
2008 User modeling and user-adapted interaction  
A critiquing-based recommender system acts like an artificial salesperson.  ...  Therefore, the results from our studies shed light support in the development of an effective and user-centric critiquing-based recommender system.  ...  Critiquing-based recommender systems Our investigation of existing critiquing-based recommender systems revealed that they basically follow a similar interaction model (see Fig. 1 ).  ... 
doi:10.1007/s11257-008-9057-x fatcat:f3xpyksimfhctdiawqj64h5tju

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Robin Burke
2012 User modeling and user-adapted interaction  
This paper surveys the landscape of actual and possible hybrid recommenders, and introduces a novel hybrid, EntreeC, a system that combines knowledge-based recommendation and collaborative filtering to  ...  To improve performance, these methods have sometimes been combined in hybrid recommenders.  ...  The interface to the Entree system was designed and created by Robin Hunicke.  ... 
doi:10.1023/a:1021240730564 fatcat:ec5rvjdj7bay3afaj5xzz6e7aa

Overview of Recommendation System: Approaches and their Prosperity

Chittineni Yashwanth Naga Sai
2020 International Journal for Research in Applied Science and Engineering Technology  
Web recommender systems are categorized into various approaches such as collaborative filtering, content based, knowledge based and hybrid recommender systems.  ...  The recommender system plays a vital role in a variety of areas like product and service-based companies.  ...  Hybrid recommender system is mainly classified into mainly: 1) Weighted Recommended System: One of the most elementary of hybrid systems.  ... 
doi:10.22214/ijraset.2020.32561 fatcat:ti5v5ck24zct3fpfngq3ztt4l4

A Framework for Building Chat-based Recommender Systems

Fedelucio Narducci, Pierpaolo Basile, Andrea Iovine, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro
2018 International Conference on Information and Knowledge Management  
In this demo, we present a framework for building chatbased recommender systems. The framework, based on a content-based recommendation algorithm, is independent from the domain.  ...  Chat-based recommender systems are getting more and more attention in recent time given their natural interaction with the user.  ...  IVA 07114250967, and PON01 00850 ASK-Health (Advanced system for the interpretations and sharing of knowledge in health care).  ... 
dblp:conf/cikm/NarducciBIGLS18 fatcat:enfkkfxmffahvhyyp4pxnbjhde

A Case-Based Reasoning Approach to Collaborative Filtering [chapter]

Robin Burke
2000 Lecture Notes in Computer Science  
Collaborative filtering systems make recommendations based on the accumulation of ratings by many users.  ...  The process has a case-based reasoning flavor: recommendations are generated by looking at the behavior of other users who are considered similar.  ...  The interface to the Entree system was designed and created by Robin Hunicke.  ... 
doi:10.1007/3-540-44527-7_32 fatcat:ik4pihdqvfbxfelet2t2ovzhku

Basic Approaches in Recommendation Systems [chapter]

Alexander Felfernig, Michael Jeran, Gerald Ninaus, Florian Reinfrank, Stefan Reiterer, Martin Stettinger
2013 Recommendation Systems in Software Engineering  
We conclude this chapter with a discussion of newer algorithmic trends, especially critiquing-based and group recommendation.  ...  Recommendation systems support users in finding items of interest.  ...  Critiquing-based recommendation systems are useful in situations where users are not experts in the item domain and prefer to specify their requirements on the level of critiques [34] .  ... 
doi:10.1007/978-3-642-45135-5_2 fatcat:wfx2duaz5vfkpazoxotx4onzb4

On the Evolution of Critiquing Recommenders [chapter]

Lorraine McGinty, James Reilly
2010 Recommender Systems Handbook  
Over the past decade a significant amount of recommender systems research has demonstrated the benefits of conversational architectures that employ critique-based interfacing (e.g., Show me more like item  ...  The critiquing phenomenon has attracted great interest in line with the growing need for more sophisticated decision/recommendation support systems to assist online users who are overwhelmed by multiple  ...  Early work in this area introduced the EntréeC hybrid recommender system [4, 5] which adds a collaborative filtering component to Entrée [6] , creating a knowledge-based/collaborative cascade hybrid  ... 
doi:10.1007/978-0-387-85820-3_13 fatcat:k4ceab67uzbg7gid42fnrsgyhm

A Hybrid Similarity Concept for Browsing Semi-structured Product Items [chapter]

Markus Zanker, Sergiu Gordea, Markus Jessenitschnig, Michael Schnabl
2006 Lecture Notes in Computer Science  
Therefore, we present a hybrid similarity approach from information retrieval and case-based recommendation systems and enrich it with additional knowledge-based concepts like threshold values and explanations  ...  Furthermore, we implemented our hybrid similarity concept in a service component and give evaluation results for the e-tourism domain.  ...  Our contribution is a hybrid framework for computing item similarity, that encompasses existing work on case-based recommendation and content-based filtering systems.  ... 
doi:10.1007/11823865_3 fatcat:h3fwjytuzbeppcvf66653oibge

Case-studies on exploiting explicit customer requirements in recommender systems

Markus Zanker, Markus Jessenitschnig
2008 User modeling and user-adapted interaction  
Recommender Systems (RS) suggest useful and interesting items to users in order to increase user satisfaction and online conversion rates.  ...  Its contribution lies in comparing different techniques such as knowledge-and utility-based methods, collaborative filtering, association rule mining as well as hybrid variants when user models consist  ...  (Burke, 2002) provides an encompassing survey of hybrid recommender systems.  ... 
doi:10.1007/s11257-008-9048-y fatcat:52ppiafdorcnthyq5sbg3yvlzm

Mining user trails in critiquing based recommenders

Skanda Raj Vasudevan, Sutanu Chakraborti
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
Critiquing based recommenders are very commonly used to help users navigate through the product space to find the required product by tweaking/critiquing one or more features.  ...  As a user interacts with such a system, trails are left behind.  ...  In [2] , a hybrid recommender is proposed adding collaborative flavor to the critiquing.  ... 
doi:10.1145/2567948.2579238 dblp:conf/www/VasudevanC14 fatcat:jx3kjw4wfndqfcddtrdcovdozi

Sentiment Analysis for Product Recommendation System Using Hybrid Algorithm

R. Umamaheswari, G. Kanimozhi
2019 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
The main goal is to recommend the products to users which are posted in E-shopping website and analyzing which one is the best and use hybrid learning algorithm which analyze various feedbacks related  ...  Finally analysis takes place based on classification. To find out fake review in the website can be analyzed.  ...  product recommendation system based on hybrid recommendation algorithm.  ... 
doi:10.32628/cseit195451 fatcat:apm6tyr5pbeqrp5lu42f2m4sr4

Conversational Recommender Systems Based on Criticism for Tourist Attractions using TF-IDF

Rayhan M Auliarahman, Z K Abdurahman Baizal, Nurul Ikhsan
2021 JURNAL MEDIA INFORMATIKA BUDIDARMA  
However, only a few studies have conducted a critique-based recommendation system using the Conversational Recommender System (CRS).  ...  Many researches on recommendation systems based on criticism have been carried out with the aim of obtaining user preferences.  ...  application. we present an online evaluation of the Hybrid-Critiquing system.  ... 
doi:10.30865/mib.v5i4.3245 fatcat:ftu5uij5ijbobmoz2ug76kgvwq
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