Conversational Recommender Systems 2018


Notes:

  • Conversational interface and dialog systems
  • Conversational recommender
  • Conversational recommenders
  • Conversational recommender system (CRS)

Wikipedia:

References:

See also:

100 Best Conversational Commerce Videos | 100 Best Recommender System Videos | Conversational Agent Timeline | Conversational Agents 2018 | Patents Search for Conversational Agents 2016 | Conversational Systems Meta Guide | Conversational Intelligence | Recommender Dialog Systems 2016


A chat-based group recommender system for tourism
TN Nguyen, F Ricci – Information Technology & Tourism, 2018 – Springer
Group recommender systems are information filtering and decision support applications that are aimed at aiding a group of users in making decisions when they are considering a set of alternatives….

“I’m looking for something like…”: Combining Narratives and Example Items for Narrative-driven Book Recommendation
T Bogers, M Koolen – … -aware and Conversational Recommender …, 2018 – vbn.aau.dk
Research on recommendation algorithms for ratings prediction and item ranking has resulted in a better understanding of these tasks and an array of algorithms with state-of-the-art performance. However, not all recommendation needs can be solved by providing a …

Vote Goat: Conversational Movie Recommendation
J Dalton, V Ajayi, R Main – The 41st International ACM SIGIR Conference …, 2018 – dl.acm.org
… In conversational recommender systems, previous work on preference elicitation [2] showed a conversational model could be effective at rapidly learning users’ preferences … Towards conversational recommender systems. In KDD, 2016 …

Enhancing the conversational process by using a logical closure operator in phenotypes implications
F Benito?Picazo, M Enciso, C Rossi… – … Methods in the …, 2018 – Wiley Online Library
… By these means, our approach is inspired in one of the solutions proposed in this field, the so-called conversational recommender systems [3]. These are closely related with the concepts of critiquing recommender systems [4] and information recommendation [5]. In these …

Incorporating user experience into critiquing-based recommender systems: a collaborative approach based on compound critiquing
H Xie, DD Wang, Y Rao, TL Wong… – International Journal of …, 2018 – Springer
… reducing the interaction effort of users. Keywords. Collaborative approach Compound critiquing Conversational recommender Retrospective user study. Download article PDF. 1 Introduction. Product recommender systems (RSs) [1 …

Understanding user interactions with podcast recommendations delivered via voice
L Yang, M Sobolev, C Tsangouri, D Estrin – Proceedings of the 12th ACM …, 2018 – dl.acm.org
… 2016. Towards conversational recommender systems. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 815– 824 … 2004. Com- pound critiques for conversational recommender systems …

Q&r: A two-stage approach toward interactive recommendation
K Christakopoulou, A Beutel, R Li, S Jain… – Proceedings of the 24th …, 2018 – dl.acm.org
… by selecting for them the right item, ie, product to buy, content to read, video to watch, at the right time [3]. Recently, recommendation researchers and practitioners have aspired to advance the frontier of recommendation by building conversational recommenders in order to …

Situation-dependent combination of long-term and session-based preferences in group recommendations: an experimental analysis
TN Nguyen, F Ricci – Proceedings of the 33rd Annual ACM Symposium …, 2018 – dl.acm.org
Page 1. Situation-Dependent Combination of Long-Term and Session-Based Preferences in Group Recommendations: An Experimental Analysis Thuy Ngoc Nguyen Free University of Bozen-Bolzano Bolzano, Italy ngoc.nguyen@unibz.it …

MusicRoBot: Towards Conversational Context-Aware Music Recommender System
C Zhou, Y Jin, K Zhang, J Yuan, S Li… – … Conference on Database …, 2018 – Springer
… Christakopoulou et al. [1] proposes a conversational recommender system for restaurant recommendation by asking user absolute or relative questions. Sun et al … References. 1. Christakopoulou, K., Radlinski, F., Hofmann, K.: Towards conversational recommender systems …

Knowledge-aware and conversational recommender systems
VW Anelli, P Basile, D Bridge, T Di Noia… – Proceedings of the 12th …, 2018 – dl.acm.org
More and more precise and powerful recommendation algorithms and techniques have been proposed over the last years able to effectively assess users’ tastes and predict information that would probably be of interest for them. Most of these approaches rely on the …

An Argumentation-based Conversational Recommender System for Recommending Learning Objects
J Palanca, S Heras, P Rodríguez Marín… – Proceedings of the 17th …, 2018 – ifaamas.org
In this paper, we present an argumentation-based Conversational Educational Recommender System (C-ERS), which helps students to find the more suitable learning resources considering their learning objectives and profile. The recommendation process is …

Improving the User Experience with a Conversational Recommender System
F Narducci, M de Gemmis, P Lops… – … Conference of the Italian …, 2018 – Springer
Chatbots are becoming more and more popular for several applications like customer care, health care, medical diagnoses. Generally, they have an interaction with users based on natural language, buttons, or both. In this paper we study the user interaction with a content …

Conversational Recommender System
Y Sun, Y Zhang – arXiv preprint arXiv:1806.03277, 2018 – arxiv.org
A personalized conversational sales agent could have much commercial potential. E-commerce companies such as Amazon, eBay, JD, Alibaba etc. are piloting such kind of agents with their users. However, the research on this topic is very limited and existing …

User-Interactive Recommender System for Electronic Products Using Fuzzy Numbers
S Sharma, CR Krishna, S Solanki, K Kaur… – Advanced Computing and …, 2018 – Springer
… sharing systems. Int. J. Syst. Sci. 34(1), 97–106 (2008)MATHGoogle Scholar. 5. Ricci, F., Nhat Nguyen, Q., Averjanova, O.: Exploiting a map-based interface in conversational recommender systems for mobile travelers. In: Sharda …

Influence of Data-Derived Individualities on Persuasive Recommendation
M Inoue, H Ueno – Asia Information Retrieval Symposium, 2018 – Springer
In this study, two machine learning based approaches have been compared that can add personal communication traits to a conversational recommender system. The first approach involves the creation of …

Picture-based navigation for diagnosing post-harvest diseases of apple
M Nocker, G Sottocornola, M Zanker, S Baric… – Proceedings of the 12th …, 2018 – dl.acm.org
… It thus builds on earlier works on picture-based navigation for conversational recommender systems and provides evidence for its usability based on a first small-scale comparative usability study … KEYWORDS Conversational Recommender System; RS in Agriculture …

Movieexplorer: building an interactive exploration tool from ratings and latent taste spaces
TT Taijala, MC Willemsen, JA Konstan – Proceedings of the 33rd Annual …, 2018 – dl.acm.org
… available (eg limiting recommendations to new movies or comedies). Dialog-based and conversational recommenders were developed to offer users greater control over exploration. Many of these systems used case-based, attribute …

Tuning a conversation strategy for interactive recommendations in a chatbot setting
Y Ikemoto, V Asawavetvutt, K Kuwabara… – Journal of Information …, 2018 – Taylor & Francis
… Boston , MA : Springer. [Google Scholar]). In these systems, the interaction between a system and a user is typically one-shot. However, in conversational recommender systems, a user repeatedly interacts with a system … Towards conversational recommender systems …

Towards Deep Conversational Recommendations
R Li, SE Kahou, H Schulz, V Michalski… – Advances in Neural …, 2018 – papers.nips.cc
… Transactions on Interactive Intelligent Systems (TiiS), 5(4):19, 2016. [6] Alessandro Suglia, Claudio Greco, Pierpaolo Basile, Giovanni Semeraro, and Annalina Caputo. An automatic procedure for generating datasets for conversational recommender systems …

Shopping Decisions Made in a Virtual World: Defining a State-Based Model of Collaborative and Conversational User-Recommender Interactions
D Contreras, M Salamo, I Rodriguez… – IEEE Consumer …, 2018 – ieeexplore.ieee.org
… online services. Previous research has focused on a collaborative conversational recommender (CCR) framework, in which a synchronous online 3-D interface for multiple consum- ers integrates with a recommender. In this …

Conversation Strategy of a Chatbot for Interactive Recommendations
Y Ikemoto, V Asawavetvutt, K Kuwabara… – Asian Conference on …, 2018 – Springer
… On the other hand, in conversational recommender systems, a user repeatedly interacts with a system … In a conversational recommender system, obtaining feedback can be categorized into two basic types: navigation by asking and navigation by proposing [10] …

Code Hunting Games: A Mixed Reality Multiplayer Treasure Hunt Through a Conversational Interface
BD Paolini, A Bogliolo – Internet Science: INSCI 2017 …, 2018 – books.google.com
… 555–565. ACM (2017) Kucherbaev, P., Psyllidis, A., Bozzon, A.: Chatbots as conversational recommender systems in urban contexts. arXiv preprint arXiv: 1706.10076 (2017) McTear, MF: The rise of the conversational interface: a new kid on the block …

Narrative-Driven Recommendation as Complex Task
T Bogers, M Koolen – Anne Dirkson, Suzan Verberne, Gerard van …, 2018 – arxiv.org
… 2018.“I’m looking for something like…”: Combining Narratives and Example Items for Narrative-driven Book Recommen- dation. In KARS’18: Proceedings of the First Knowledge-aware and Conversational Recommender Systems Workshop. CEUR-WS …

VISUALIZATION, CONFIGURATION AND AUTOMATED TESTING OF A NATURAL LANGUAGE PROCESSING APPLICATION FOR CONVERSATIONAL …
R Ramkumar – ncrdsims.edu.in
… Piscataway, NJ, USA, 221-225. [20] DH Widyantoro and ZKA Baizal, “A framework of conversational recommender system based on user functional requirements,” 2014 2nd International Conference on Information and Communication Technology (ICoICT), Bandung …

A Multi-Level Genetic Algorithm Approach for Generating Efficient Travel Plans
FH Prabowo, KM Lhaksmana… – 2018 6th International …, 2018 – ieeexplore.ieee.org
… A tourist recommender system application will greatly help tourists by providing destination information and travel planning features. This research is a part of the development of conversational recommender system in the field of tourism …

A Cognitively Inspired Clustering Approach for Critique-Based Recommenders
D Contreras, M Salamó – Cognitive Computation – Springer
… search for a desired product as they are immersed in a 3D virtual environment that enhances their buying experience as well as increas- ing the interaction elements for eliciting user feedback [6]. This recommender is called Collaborative Conversational Recommender (CCR) …

Context-aware recommender system based on ontology for recommending tourist destinations at Bandung
LRH Arigi, ZKA Baizal, A Herdiani – Journal of Physics …, 2018 – iopscience.iop.org
… Systems with Applications, vol. 39, no. 4, p 3995-4006 [12] Baizal ZA and Murti Y 2017 Evaluating functional requirements-based compound critiquing on conversational recommender system. In Information and Communication …

Data-driven decision making in critique-based recommenders: from a critique to social media data
D Contreras, M Salamó – Journal of Intelligent Information Systems – Springer
Page 1. Journal of Intelligent Information Systems https://doi.org/10.1007/s10844-018- 0520-9 Data-driven decision making in critique-based recommenders: from a critique to social media data David Contreras1 ·Maria Salam ó2,3 …

Advanced Interaction and Virtual\/Augmented Reality: Making Interaction with Machines More Natural and Effective
F Lamberti, F Pescador – IEEE Consumer Electronics Magazine, 2018 – ieeexplore.ieee.org
… In the final article, “Implementation and Evaluation of a Collaborative Conversational Recommender in a 3-D Virtual World,” Contreras et al. focus on recommender systems used, eg, by home electronics devices to deliver online personal- ized services …

Multi-channel Conversational Agent for Personalized Music Recommendations
M Morisio, G Verazzo – webthesis.biblio.polito.it
Page 1. POLITECNICO DI TORINO Master degree course in Computer engineering Master Degree Thesis Multi-channel Conversational Agent for Personalized Music Recommendations Supervisor: Prof. Maurizio Morisio Candidate Giulio Verazzo Student id: 225208 …

Towards the next generation of multi-criteria recommender systems
Z Li – Proceedings of the 12th ACM Conference on …, 2018 – dl.acm.org
… recom- mendation [28], music recommendation [16], and conversational recommender systems [49], Recurrent Neural Networks (RNNs) and Deep Structured Semantic Models (DSSMs) are also widely ap- plied. As a novel …

Smart Entertainment-A Critiquing Based Dialog System for Eliciting User Preferences and Making Recommendations
RR Ramnani, S Sengupta, TR Ravilla… – … on Applications of Natural …, 2018 – Springer
… In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (2013)Google Scholar. 7. Zhang, J., Pu, P.: A comparative study of compound critique generation in conversational recommender systems …

The Technological Gap Between Virtual Assistants and Recommendation Systems
D Rafailidis – arXiv preprint arXiv:1901.00431, 2018 – arxiv.org
… 2015. [3] Yueming Sun and Yi Zhang. Conversational recommender system. In The … 2018. [4] Konstantina Christakopoulou, Filip Radlinski, and Katja Hofmann. To- wards conversational recommender systems. In Proceedings …

Following the Advent of the Internet, the Blockchain May Revolutionize Consumer Electronics
SP Mohanty, S Healthcare, PA Choreographer – 2018 – researchgate.net
… Implementation and Evaluation of a Collaborative Conversational Recommender in a 3D Virtual World: This article presents a state-based model of user-recommender interaction for allowing users for different states of interaction in a 3D virtual world facility …

Handling preferences
A Felfernig, L Boratto, M Stettinger, M Tkal?i? – Group Recommender …, 2018 – Springer
… 51–69MATHGoogle Scholar. 13. K. Christakopoulou, F. Radlinski, K. Hofmann, Towards conversational recommender systems, in International Conference on Knowledge Discovery and Data Mining (KDD 2016), San Francisco, CA, USA (2016), pp. 815–824Google Scholar …

Why Did Naethan Pick Android over Apple? Exploiting Trade-offs in Learning User Preferences
A Sekar, D Ganesan, S Chakraborti – International Conference on Case …, 2018 – Springer
… in three recommendation domains. Keywords. Case-based recommendation Conversational recommender systems Trade-offs Preference feedback Diversity. Download conference paper PDF. 1 Introduction. A central goal of …

Advances in Artificial Intelligence
C Ghidini, B Magnini, A Passerini, P Traverso – Springer
… 502 Mauro Dragoni Novelty-Aware Matrix Factorization Based on Items’ Popularity….. 516 Ludovik Coba, Panagiotis Symeonidis, and Markus Zanker Improving the User Experience with a Conversational Recommender System …

Eliciting pairwise preferences in recommender systems
S Kalloori, F Ricci, R Gennari – … of the 12th ACM Conference on …, 2018 – dl.acm.org
Page 1. Eliciting Pairwise Preferences in Recommender Systems Saikishore Kalloori, Francesco Ricci and Rosella Gennari Free University of Bozen – Bolzano, Italy Piazza Domenicani 3, I – 39100, Bolzano, Italy ksaikishore@unibz.it,fricci@unibz.it,gennari@inf.unibz.it …

Group Recommender Systems: An Introduction
A Felfernig, L Boratto, M Stettinger, M Tkal?i? – 2018 – Springer
Page 1. SPRINGER BRIEFS IN ELECTRICAL AND COMPUTER ENGINEERING Alexander Felfernig · Ludovico Boratto Martin Stettinger · Marko Tkal?i? Group Recommender Systems An Introduction Page 2. SpringerBriefs in Electrical and Computer Engineering …

Context Based-Tourism Recommender System: Towards Tourists’ Context-Sensitive Preference Conceptual Model
KA Achmad, LE Nugroho… – 2018 4th International …, 2018 – ieeexplore.ieee.org
Page 1. Context based-Tourism Recommender System: Towards Tourists’ Context-Sensitive Preference Conceptual Model Kusuma Adi Achmad Dept. of Electrical Engineering and Information Technology Universitas Gadjah Mada Yogyakarta, Indonesia kadia@mail.ugm.ac …

Active Learning in Recommendation Systems with Multi-level User Preferences
Y Bu, K Small – arXiv preprint arXiv:1811.12591, 2018 – arxiv.org
Page 1. Active Learning in Recommendation Systems with Multi-level User Preferences Yuheng Bu ? Kevin Small † Abstract While recommendation systems generally observe user be- havior passively, there has been an increased …

A Fast Learning Recommender Estimating Preferred Ranges of Features
T Watanabe, Y Nakazato, H Muroi, T Hashimoto… – Joint Conference on …, 2018 – Springer
… social recommender systems. Comput. Commun. 41, 1–10 (2014)CrossRefGoogle Scholar. 18. Zhang, J., Pu, P.: A comparative study of compound critique generation in conversational recommender systems. In: Proceedings of …

Towards an Optimal Dialog Strategy for Information Retrieval Using Both Open-and Close-ended Questions
Y Zhang, QV Liao, B Srivastava – 23rd International Conference on …, 2018 – dl.acm.org
… 1990. Conversation as direct manipulation: An iconoclastic view. (1990). 2. Konstantina Christakopoulou, Filip Radlinski, and Katja Hofmann. 2016. Towards Conversational Recommender Systems.. In KDD. 815–824. 3. Jennifer Chu-Carroll. 2000 …

A state-of-the-art Recommender Systems: An overview on Concepts, Methodology and Challenges
P Jariha, SK Jain – 2018 Second International Conference on …, 2018 – ieeexplore.ieee.org
… 293, pp.235–250. 2015 [25] K. Christakopoulou F. Radlinski and K. Hofmann. Towards Conversational Recommender System, In KDD, 2016, 815-824. ACM 2016 [26] X. Zhao W. Zhang and J. Wang: Interactive collaborative filtering …

Recommending Crowdsourced Trips on wOndary
LW Dietz, A Weimert – RecTour 2018, 2018 – ec.tuwien.ac.at
… org/10.1007/978-0-387-85820-3_13 [20] Lorraine McGinty and Barry Smyth. 2006. Adaptive Selection: An Analysis of Critiquing and Preference-Based Feedback in Conversational Recommender Systems. International Journal of Electronic Commerce 11, 2 (Dec. 2006), 35 …

Eliciting User Food Preferences in terms of Taste and Texture in Spoken Dialogue Systems
J Zeng, YI Nakano, T Morita, I Kobayashi… – Proceedings of the 3rd …, 2018 – dl.acm.org
… [20] Pontus Wärnestål, Lars Degerstedt, and Arne Jönsson. 2007. Interview and deliv- ery: Dialogue strategies for conversational recommender systems. In Proceedings of the 16th Nordic Conference of Computational Linguistics (NODALIDA 2007). 199–205 …

Effects of individual traits on diversity-aware music recommender user interfaces
Y Jin, N Tintarev, K Verbert – Proceedings of the 26th Conference on …, 2018 – dl.acm.org
… To remedy the limitation of imposing diversity on an existing system, McGint et al. [27] demonstrate an adaptive diversity-enhancing algorithm in a conversational recommender system. Most of these algorithms improve diversity for a ranked list …

Algorithms for Group Recommendation
A Felfernig, L Boratto, M Stettinger, M Tkal?i? – Group Recommender …, 2018 – Springer
… Some user preferences are already known from previous recommendation sessions, and so do not need to be determined in an iterative process. In contrast, conversational recommender systems [10, 12, 18, 42, 47, 49] engage users in a dialog to elicit user preferences …

BYU-EVE: Mixed Initiative Dialog via Structured Knowledge Graph Traversal and Conversational Scaffolding
N Fulda, T Etchart, W Myers, D Ricks, Z Brown… – dex-microsites-prod.s3.amazonaws …
Page 1. BYU-EVE: Mixed Initiative Dialog via Structured Knowledge Graph Traversal and Conversational Scaffolding Nancy Fulda, Tyler Etchart, William Myers, Daniel Ricks, Zachary Brown Joseph Szendre, Ben Murdoch, Andrew Carr and David Wingate …

A Survey on Reducing the Semantic Gap in Content Based Image Retrieval System
N Sathya, S Rathi – … Journal of Advanced Studies in Computers …, 2018 – search.proquest.com
… D. Relevance Feedback and Collaborative Image Retrieval Techniques Preference Based Feedback is used in collaborative image retrieval [8]. Preference based recommendation uses conversational recommender system which interacts with the user as like the conversation …

Interactive Storytelling for Movie Recommendation through Latent Semantic Analysis
K Wegba, A Lu, Y Li, W Wang – 23rd International Conference on …, 2018 – dl.acm.org
… In addition, explanation interfaces can provide system trans- parency and thus increase user acceptance [46, 8]. Also related to this work is conversational recommender sys- tems [7, 9], which intelligently select what information to elicit from the user in different situations …

Knowledge-aware Autoencoders for Explainable Recommender Systems
V Bellini, A Schiavone, T Di Noia, A Ragone… – Proceedings of the 3rd …, 2018 – dl.acm.org
Page 1. Knowledge-aware Autoencoders for Explainable Recommender Systems Vito Bellini ? , Angelo Schiavone ? , Tommaso Di Noia ? , Azzurra Ragone•, Eugenio Di Sciascio ? ? Polytechnic University of Bari Bari – Italy …

Deriving item features relevance from collaborative domain knowledge
MF Dacrema, A Gasparin, P Cremonesi – arXiv preprint arXiv:1811.01905, 2018 – arxiv.org
… 2018. Deriving item features relevance from collaborative domain knowledge. In Proceedings of KaRS 2018 Workshop on Knowledge-aware and Conversational Recommender Systems (KaRS @RecSys 2018). ACM, New York, NY, USA, 4 pages …

OpenRec: A Modular Framework for Extensible and Adaptable Recommendation Algorithms
L Yang, E Bagdasaryan, J Gruenstein… – Proceedings of the …, 2018 – dl.acm.org
… rithm module for implicit feedback. • For interactive and conversational recommender systems, the optimizers can be designed to update user and item represen- tations in the active-learning se ings [34]. For every iteration, a …

Transparency in Fair Machine Learning: the Case of Explainable Recommender Systems
B Abdollahi, O Nasraoui – Human and Machine Learning, 2018 – Springer
… https://doi.org/10.1007/s10464-007-9108-14. 36. Lipton, ZC: The Mythos of Model Interpretability (2016). arXiv preprint arXiv:1606.03490. 37. McCarthy, K., Reilly, J., McGinty, L., Smyth, B.: Thinking positively-explanatory feedback for conversational recommender systems …

A recommender approach based on customer emotions
E Poirson, C Da Cunha – Expert Systems with Applications, 2018 – Elsevier
Skip to main content …

Investigating how conversational search agents affect user’s behaviour, performance and search experience
M Dubiel, M Halvey, L Azzopardi… – The Second …, 2018 – strathprints.strath.ac.uk
Page 1. Dubiel, Mateusz and Halvey, Martin and Azzopardi, Leif and Daronnat, Sylvain (2018) Investigating how conversational search agents affect user’s behaviour, performance and search experience. In: The Second International …

Categorical-attributes-based item classification for recommender systems
Q Zhao, J Chen, M Chen, S Jain, A Beutel… – Proceedings of the 12th …, 2018 – dl.acm.org
Page 1. Categorical-Attributes-Based Item Classification for Recommender Systems Qian Zhao? University of Minnesota Minneapolis, Minnesota, United States zhaox331@umn.edu Jilin Chen, Minmin Chen, Sagar Jain Alex Beutel, Francois Belletti, Ed H. Chi Google Inc …

Conceptualizing agent-human interactions during the conversational search process
L Azzopardi, M Dubiel, M Halvey… – … to Information Retrieval, 2018 – strathprints.strath.ac.uk
Page 1. Azzopardi, Leif and Dubiel, Mateusz and Halvey, Martin and Dalton, Jeffery (2018) Conceptualizing agent-human interactions during the conversational search process. In: The Second International Workshop on Conversational …

On Querying for Safe Optimality in Factored Markov Decision Processes
S Zhang, EH Durfee, S Singh – … of the 17th International Conference on …, 2018 – dl.acm.org
… 1127–1133. [16] Paolo Viappiani and Craig Boutilier. 2009. Regret-based optimal recommendation sets in conversational recommender systems. In Proceedings of the Third ACM Conference on Recommender Systems. 101–108 …

Learning to Interact with Users: A Collaborative-Bandit Approach
K Christakopoulou, A Banerjee – Proceedings of the 2018 SIAM International …, 2018 – SIAM
Page 1. Learning to Interact with Users: A Collaborative-Bandit Approach ? Konstantina Christakopoulou and Arindam Banerjee† Abstract Learning to interact with users and discover their preferences is central in most web …

Towards Conversational Search and Recommendation: System Ask, User Respond
Y Zhang, X Chen, Q Ai, L Yang, WB Croft – Proceedings of the 27th ACM …, 2018 – dl.acm.org
Page 1. Towards Conversational Search and Recommendation: System Ask, User Respond Yongfeng Zhang1, Xu Chen2, Qingyao Ai3, Liu Yang3, W. Bruce Croft3 1Department of Computer Science, Rutgers University, New …

Multi-Clustering in Fast Collaborative Filtering Recommender Systems
U Kuzelewska – ICSEA 2018, 2018 – researchgate.net
… 5, pp. 11–32, 2001. [4] K. McCarthy, J. Reilly, L. McGinty, and B. Smyth,“Thinking positively- explanatory feedback for conversational recommender systems,” in Proceedings of the European Conference on Case-Based Reasoning (ECCBR-04), 2004, pp. 115–124 …

Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning
X Zhao, L Zhang, Z Ding, L Xia, J Tang… – arXiv preprint arXiv …, 2018 – arxiv.org
Page 1. Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning Xiangyu Zhao Data Science and Engineering Lab Michigan State University zhaoxi35@msu. edu Liang Zhang Data Science Lab JD.com zhangliang16@jd.com …

Applications of big social media data analysis: An overview
MA Al-garadi, G Mujtaba, MS Khan… – Computing …, 2018 – ieeexplore.ieee.org
… 2016, pp. 223-228. [10] T. Mahmood, G. Mujtaba, and A. Venturini, “Dynamic personalization in conversational recommender systems,” Information Systems and e-Business Management, vol. 12, pp. 213-238, 2014. [11] MA …

Allyn, A Recommender Assistant for Online Bookstores
L Esquerrà Schaefer – 2018 – upcommons.upc.edu
Page 1. Degree in Statistics Degree in Economics Title: Allyn, A Recommender Assistant for Online Bookstores Author: Laia Esquerrà Schaefer Statistics Advisor: Esteban Vegas Lozano Department: Genètica, Microbiologia i Estadística, secció d’Estadística …

No more ready-made deals: constructive recommendation for telco service bundling
P Dragone, G Pellegrini, M Vescovi, K Tentori… – Proceedings of the 12th …, 2018 – dl.acm.org
… Dragone et al. This is the typical setting in which “conversational” recommender systems are employed [44], and the utility function is learned via user interaction in a process commonly known as preference elic- itation [3–6, 9, 33] …

Explanations for Groups
A Felfernig, L Boratto, M Stettinger, M Tkal?i? – Group Recommender …, 2018 – Springer
Explanations are used in recommender systems for various reasons. Users have to be supported in making (high-quality) decisions more quickly. Developers of recommender systems want to convince users…

Generating Travel Itinerary Using Ant Collony Optimization.
ZK Abdurahman Baizal, AA Rahmawati… – …, 2018 – search.ebscohost.com
… 1997: 1(1):53–66. [15] Baizal Z. A, Widyantoro DH, and Maulidevi N U. Factors Influencing User?s Adoption of Conversational Recommender System Based on Product Functional Requirements. TELKOMNIKA (Telecommunication Computing Electronics and Control) …

Chatbol, a chatbot for the Spanish “La Liga”
C Segura, A Palau, J Luque, M Costa-jussa, R Banchs – 2018 – oar.a-star.edu.sg
… 20. Alessandro Suglia, Claudio Greco, Pierpaolo Basile, Giovanni Semeraro, and Annalina Ca- puto. An automatic procedure for generating datasets for conversational recommender sys- tems. CLEF, 2017. 21. Jörg Tiedemann …

A CLUSTERING APPROACH FOR PRODUCT RECOMMENDATION SYSTEM IN E-COMMERCE USING SENTIMENT AND SIMILARITY OPINION MINING
D Benarji Tharini, VV Bulusu – ijamtes.org
… filtering or classification. As such our work can be framed in the context of past approaches for case-based product recommendation including conversational recommender’s critiquing-based techniques [12], for example. For the …

Deep Reinforcement Learning for Page-wise Recommendations
X Zhao, L Xia, L Zhang, Z Ding, D Yin… – arXiv preprint arXiv …, 2018 – arxiv.org
Page 1. Deep Reinforcement Learning for Page-wise Recommendations Xiangyu Zhao Data Science and Engineering Lab Michigan State University zhaoxi35@msu. edu Long Xia Data Science Lab JD.com xialong@jd.com …

A Developed Collaborative Filtering Similarity Method to Improve the Accuracy of Recommendations under Data Sparsity
H Al-Bashiri, MA Abdulgabber, R Awanis… – … Journal of Advanced …, 2018 – umpir.ump.edu.my
… Vol. 9, No. 4, 2018 141 | P age www.ijacsa.thesai.org [9] YR Murti and Z. Baizal, “Compound Critiquing for Conversational Recommender System Based on Functional Requirement,” Advanced Science Letters. vol. 22, pp. 1892-1896, 2016. [10] S. Sivapalan, et al …

Decision Tasks and Basic Algorithms
A Felfernig, L Boratto, M Stettinger, M Tkal?i? – Group Recommender …, 2018 – Springer
Recommender systems are decision support systemshelping users to identify one or more items (solutions) that fit their wishes and needs. The most frequent application of recommender systems nowadays…

Preference elicitation as an optimization problem
A Sepliarskaia, J Kiseleva, F Radlinski… – Proceedings of the 12th …, 2018 – dl.acm.org
Page 1. Preference Elicitation as an Optimization Problem Anna Sepliarskaia University of Amsterdam Amsterdam, The Netherlands a.sepliarskaia@uva.nl Julia Kiseleva University of Amsterdam Amsterdam, The Netherlands y.kiseleva@uva.nl …

Face Value?
A Shamekhi, QV Liao, D Wang, RKE Bellamy… – Proceedings of the …, 2018 – dl.acm.org
Page 1. Face Value? Exploring the Effects of Embodiment for a Group Facilitation Agent Ameneh Shamekhi1*,Q. Vera Liao2, Dakuo Wang2, Rachel KE Bellamy2, Thomas Erickson2 1Northeastern University, Boston, MA, USA …

Towards a Reference Architecture for Augmentative and Alternative Communication Systems
N Franco, E Silva, R Lima, R Fidalgo – Brazilian Symposium on Computers …, 2018 – br-ie.org
… We highlight that the theory of scripts can also be regarded as a prediction technique since a given script can be employed to implement a conversational recommender [Hernández et al. 2014] that makes suggestions and refinements based on the user’s feedbacks …

Interactive recommendation via deep neural memory augmented contextual bandits
Y Shen, Y Deng, A Ray, H Jin – … of the 12th ACM Conference on …, 2018 – dl.acm.org
Page 1. Interactive Recommendation via Deep Neural Memory Augmented Contextual Bandits Yilin Shen, Yue Deng, Avik Ray, Hongxia Jin Samsung Research America, Mountain View, CA, USA {yilin.shen,y1.deng,avik.r,hongxia.jin}@samsung.com …

An improved memory-based collaborative filtering method based on the TOPSIS technique
H Al-Bashiri, MA Abdulgabber, A Romli, H Kahtan – PloS one, 2018 – journals.plos.org
This paper describes an approach for improving the accuracy of memory-based collaborative filtering, based on the technique for order of preference by similarity to ideal solution (TOPSIS) method. Recommender systems are used to filter the huge amount of data available online …

INTERACTIVE ONLINE LEARNING WITH INCOMPLETE KNOWLEDGE
Q Wu – 2018 – people.virginia.edu
… Proactive user-system interaction not only involves encouraging the most informative actions but also the most informative users. There is a recent attempt on interactive question selection using bandit learning solution in conversational recommender systems [18] …

AI-VT: An Example of CBR that Generates a Variety of Solutions to the Same Problem
J Henriet, F Greffier – International Conference on Case-Based Reasoning, 2018 – Springer
… 3–15. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61030-6_1CrossRefGoogle Scholar. 15. McGinty, L., Smyth, B.: On the role of diversity in conversational recommender systems. In: Ashley, KD, Bridge, DG (eds.) ICCBR 2003. LNCS (LNAI), vol. 2689, pp …

Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making
LM Zintgraf, DM Roijers, S Linders, CM Jonker… – arXiv preprint arXiv …, 2018 – arxiv.org
Page 1. Ordered Preference Elicitation Strategies for Supporting Multi-Objective Decision Making Luisa M Zintgraf Vrije Universiteit Brussel University of Oxford Diederik M Roijers Vrije Universiteit Brussel Vrije Universiteit Amsterdam …

User participation game in collaborative filtering
L Xu, C Jiang, Y Qian, Y Ren, L Xu, C Jiang, Y Qian… – Data Privacy …, 2018 – Springer
Page 1. Chapter 5 User Participation Game in Collaborative Filtering Abstract One of the most important applications of data mining is personalized recommendation. User participation plays a vital role in personalized recommen …

Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes.
S Zhang, EH Durfee, SP Singh – IJCAI, 2018 – ijcai.org
Page 1. Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes Shun Zhang, Edmund H. Durfee, and Satinder Singh Computer Science and Engineering, University of Michigan {shunzh,durfee,baveja}@umich.edu Abstract …

Positional Scoring Rules with Uncertain Weights
P Viappiani – International Conference on Scalable Uncertainty …, 2018 – Springer
Positional scoring rules are frequently used for aggregating rankings (for example in social choice and in sports). These rules are highly sensitive to the weights associated to positions: depending…

Evaluating attributed personality traits from scene perception probability
H Zhu, L Li, S Zhao, H Jiang – Pattern Recognition Letters, 2018 – Elsevier
… Pattern Recogn. Lett. (2018), 10.1016/j.patrec.2018.03.006. [12] BD Carolis, MD Gemmis, P. Lops, G. PalestraRecognizing users feedback from non-verbal communicative acts in conversational recommender systems. Pattern Recogn. Lett., 99 (2017), pp …

Constructive Preference Elicitation
P Dragone, S Teso, A Passerini – Frontiers in Robotics and AI, 2018 – frontiersin.org
When faced with large or complex decision problems, human decisionmakers (DM) can make costly mistakes, due to inherent limitations oftheir memory, attention and knowledge. Preference elicitation toolsassist the decision maker in overcoming these limitations. They do soby …

Privacy in social information access
BP Knijnenburg – Social Information Access, 2018 – Springer
Social information access (SIA) systems crucially depend on user-provided information, and must therefore provide extensive privacy provisions to encourage users to share their personal data. Even…

Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study
G Mujtaba, L Shuib, RG Raj, R Rajandram… – Journal of forensic and …, 2018 – Elsevier
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Efficient elicitation of software configurations using crowd preferences and domain knowledge
Y Gonzalez-Fernandez, S Hamidi, S Chen… – Automated Software …, 2018 – Springer
Page 1. Automated Software Engineering https://doi.org/10.1007/s10515-018-0247-4 Efficient elicitation of software configurations using crowd preferences and domain knowledge Yasser Gonzalez-Fernandez1 · Saeideh Hamidi1 · Stephen Chen1 · Sotirios Liaskos1 …

User Participation in Collaborative Filtering-Based Recommendation Systems: A Game Theoretic Approach
L Xu, C Jiang, Y Chen, Y Ren… – IEEE Transactions on …, 2018 – ieeexplore.ieee.org
Page 1. This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON CYBERNETICS 1 User Participation in Collaborative Filtering-Based …

A Recommendation Method for Social Collaboration Tasks Based on Personal Social Preferences
J Wang, Z Wang, J Li – IEEE Access, 2018 – ieeexplore.ieee.org
Page 1. 2169-3536 (c) 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org …

Scalable and Efficient Probabilistic Topic Model Inference for Textual Data
M Magnusson – 2018 – books.google.com
Page 1. Linköping Studies in Arts and Sciences No. 743 Linköping Studies in Statistics No. 14 Scalable and Efficient Probabilistic Topic Model Inference for Textual Data Måns Magnusson Page 2. Faculty of Arts and Sciences Dissertations, No …

System-Level Design of GPU-Based Embedded Systems
A Maghazeh – 2018 – books.google.com
Page 1. Linköping Studies in Science and Technology. Dissertations. No. 1964 System-Level Design of GPU-Based Embedded Systems Arian Maghazeh Page 2. Linköping Studies in Science and Technology. Dissertations. No …

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