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Bridging memory-based collaborative filtering and text retrieval

Alejandro Bellogín, Jun Wang, Pablo Castells
2012 Information retrieval (Boston)  
In this regard, we propose a unified formulation under a common notational framework for memory-based collaborative filtering, and a technique to use any text retrieval weighting function with collaborative  ...  Specifically, major collaborative filtering algorithms, such as the memory-based, essentially calculate the dot product between the user vector (as the query vector in text retrieval) and the item rating  ...  Acknowledgements This work is supported by the Spanish Government (TIN2011-28538-C02-01) and the Regional Government of Madrid (S2009TIC-1542).  ... 
doi:10.1007/s10791-012-9214-z fatcat:z6ujthrrabbqvbfblmmjzvp43i

A Recommender Agent for Software Libraries: An Evaluation of Memory-Based and Model-Based Collaborative Filtering

Frank McCarey, Mel Cinneide, Nicholas Kushmerick
2006 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology  
In this paper we detail our RASCAL agent and describe two recommendation techniques; namely Model-Based and Memory-Based Collaborative Filtering.  ...  We are interested in producing a scalable and efficient realtime recommender and thus ideally would favor a Model-Based approach.  ...  With this mind we will investigate, compare and evaluate two CF algorithms in this paper, memory-based and model-based collaborative filtering.  ... 
doi:10.1109/iat.2006.23 dblp:conf/iat/McCareyCK06 fatcat:kvsispkjyndxlasugcwotjzrtu

Knowledge reuse for software reuse

Frank McCarey, Mel Ó Cinnéide, Nicholas Kushmerick
2008 Web Intelligence and Agent Systems  
This novel recommendation approach applies and extends commonly used Information Retrieval and Information Filtering techniques such as Collaborative Filtering, Content-Based Filtering, and Bayesian Clustering  ...  This paper advocates that component-based reuse can be supported through knowledge collaboration.  ...  Acknowledgements Funding for this research was provided by the Irish Research Council for Science, Engineering and Technology (IRCSET) under grant RCS/2003/127.  ... 
doi:10.3233/wia-2008-0130 fatcat:et3upoefuvgfpiaa2jhzmsg7me

Who's Who – A Linked Data Visualisation Tool for Mobile Environments [chapter]

A. Elizabeth Cano, Aba-Sah Dadzie, Melanie Hartmann
2011 Lecture Notes in Computer Science  
Reduced size in hand-held devices imposes significant usability and visualisation challenges.  ...  Semantic adaptation to specific usage contexts is a key feature for overcoming usability and display limitations on mobile devices.  ...  The state of the art focuses on text-based browsing and querying of LD on desktop browsers, e.g., Sig.ma [8] and Marbles [1] , targeted predominantly at technical experts (see also [2] ).  ... 
doi:10.1007/978-3-642-21064-8_33 fatcat:gtlc4bzrmzfrvlqkrukb5e6mwy

Progress in Information Retrieval [chapter]

Mounia Lalmas, Stefan Rüger, Theodora Tsikrika, Alexei Yavlinsky
2006 Lecture Notes in Computer Science  
has also continued to make inroads into areas such as Genomics, Multimedia, Peer-to-Peer and XML retrieval.  ...  This paper summarises the scientific work presented at the 28th European Conference on Information Retrieval and demonstrates that the field has not only significantly progressed over the last year but  ...  Jun Wang, Arjen P. de Vries, and Marcel J. T. Reinders. A user-item relevance model for log-based collaborative filtering.  ... 
doi:10.1007/11735106_1 fatcat:74ltdd2pkfeedbvrmtjrai5q3e

Neural Networks for Information Retrieval [article]

Tom Kenter and Alexey Borisov and Christophe Van Gysel and Mostafa Dehghani and Maarten de Rijke and Bhaskar Mitra
2018 arXiv   pre-print
The aim of this full-day tutorial is to give a clear overview of current tried-and-trusted neural methods in IR and how they benefit IR.  ...  The amount of information available can be overwhelming both for junior students and for experienced researchers looking for new research topics and directions.  ...  We cover learning of item (products, users) embeddings [4, 17, 51] , as well as deep collaborative filtering using different deep learning techniques and architectures [7, 54] .  ... 
arXiv:1801.02178v1 fatcat:c3kevelcrffodift2vvwnoscjq

Content Based Image Retrieval for Medical Images Techniques and Storage Methods-Review Paper

Prof. K. Wanjale, Tejas Borawake, Shashideep Chaudhari
2010 International Journal of Computer Applications  
The complementary nature of text and visual image features for retrieval promises to lead to good retrieval results.  ...  Some common measures for capturing the texture of images are wavelets and Gabor filters where Gabor filters perform better and correspond well to.  ... 
doi:10.5120/394-587 fatcat:5myddn572fa6zjlpgn56jzgf6a

A critical assessment of hypertext systems

G. Fischer, S. Weyer, W. P. Jones, A. C. Kay, W. Kintsch
1988 Proceedings of the SIGCHI conference on Human factors in computing systems - CHI '88  
Rather than thinking of the system as containing information, think of it as an environment for descriptions and programs.  ...  Rather than thinking of the system as a passive entity on which the author performs neural surgery to add new components and connections, think of it as an active partner --a hyperknowledge assistant.  ...  computer-based information retrieval systems (the ME system adopts a network approach and actively models the user's own memory for the files of a personal directory.)  ... 
doi:10.1145/57167.57205 fatcat:x5pr64kzlvhtljetxchgqzy4m4

Collaborative Memory Network for Recommendation Systems

Travis Ebesu, Bin Shen, Yi Fang
2018 The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18  
Deep learning has revolutionized many research fields and there is a recent surge of interest in applying it to collaborative filtering (CF).  ...  We propose Collaborative Memory Networks (CMN), a deep architecture to unify the two classes of CF models capitalizing on the strengths of the global structure of latent factor model and local neighborhood-based  ...  collaborative filtering methods.  ... 
doi:10.1145/3209978.3209991 dblp:conf/sigir/EbesuSF18 fatcat:dixbrvd6o5gd5kqziruxyn2hb4

Page 3221 of Psychological Abstracts Vol. 86, Issue 8 [page]

1999 Psychological Abstracts  
* Hemispheric dif- ferences in memory * False memories * Enhancing retrieval * Bridging the canyon ° For further reading * Notes * Glossary * References * Acknow- ledgments * About the author ¢ Index  ...  It also introduces reliable and valid measures that can be used for assessing spirituality and provides examples of spiritually based interventions and collaborations that can enhance successful treatment  ... 

Lessons for the Future from a Decade of Informedia Video Analysis Research [chapter]

Alexander G. Hauptmann
2005 Lecture Notes in Computer Science  
The base technology developed by the Informedia project combines speech, image and natural language understanding to automatically transcribe, segment and index broadcast video for intelligent search and  ...  image retrieval.  ...  Shah, Tat-Seng Chua and many other participants.  ... 
doi:10.1007/11526346_1 fatcat:h5pd3twzwraxniomnqofh6qaxq

Relevance-based language modelling for recommender systems

Javier Parapar, Alejandro Bellogín, Pablo Castells, Álvaro Barreiro
2013 Information Processing & Management  
These techniques, although well known in the Information Retrieval field, have not been applied yet to recommender systems, and, as the empirical evaluation results show, both proposals outperform individually  ...  These models achieve state-of-the-art retrieval performance in the pseudo relevance feedback task.  ...  , based on the history of similar users; and hybrid approaches, based on combining content-based recommendation and collaborative filtering.  ... 
doi:10.1016/j.ipm.2013.03.001 fatcat:d46d3t7ryjdujeyrpyd7rwt7ym

Searching in the Context of a Task: A Review of Methods and Tools

Ana Maguitman
2018 CLEI Electronic Journal  
It discusses major difficulties encountered in the research area of context-based information retrieval and presents an overview of tools proposed since the mid-nineties to deal with the problem of context-based  ...  It can also be used to filter and rank results as well as to select domain-specific search engines with better capabilities to satisfy specific information requests.  ...  Acknowledgment This work was supported by CONICET (PIP 11220120100487), MinCyT (PICT 2014-0624) and Universidad Nacional del Sur (PGI-UNS 24/N039).  ... 
doi:10.19153/cleiej.21.1.1 fatcat:eteqn6owzbbexmvo6sqfkcqywu

RecBench

Justin J. Levandoski, Michael D. Ekstrand, Michael J. Ludwig, Ahmed Eldawy, Mohamed F. Mokbel, John T. Riedl
2011 Proceedings of the VLDB Endowment  
recommenders are superior at more complex recommendation tasks such as providing filtered recommendations and blending text-search with recommendation prediction scores.  ...  This study is the first of its kind, and our findings reveal an interesting trade-off: "hand-built" recommenders exhibit superior performance in model-building and pure recommendation tasks, while DBMS-based  ...  For item-based collaborative filtering, initialization involves building the item-based model.  ... 
doi:10.14778/3402707.3402729 fatcat:wn5raoht5vectdwe3n3bsyngmq

Managing Divergent Information: Enhancing Document Expressiveness

F. Antunes, J.P. Costa, P. Macas
2006 Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06)  
resources, as a means for reinforcing the connection between distributed collaboration, decision-making and knowledge management, by enhancing document expressiveness (its persistence and linking).  ...  Though several approaches can deal with this situation, none of them aims directly at knowledge management or organizational memory creation.  ...  the central memory and retrieve its content, if possible.  ... 
doi:10.1109/hicss.2006.264 dblp:conf/hicss/AntunesCM06 fatcat:izxw2zrn7vfovh5wv54a5xioyu
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