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Page 64 of Library & Information Science Abstracts Vol. , Issue 10 [page]

1994 Library & Information Science Abstracts  
(SE) 9410413 Retrieval expectations, cluster-based effectiveness, and performance standards in the CF database. W. M. Shaw.  ...  Desccribes th methods used to investigate retrieval performance of controlled and uncontrolled subject representations as a function of retrieval expectations in the cystic fibrosis (CF) database, a sub  ... 

Design of an Architecture for Optimizing Image Retrieval by using Genetic Algorithm

S.Selvam S.Selvam, S.Thabasukannan S.Thabasukannan
2015 Communications on Applied Electronics  
The proposed method is experimental and analyzed with large database. The result show that the architecture of new CBIR system shown good performance in speed and reducing the computational time.  ...  Image retrieval plays a vital role in image processing.  ...  results and the users' expectation .They have used color attributes like the mean value, standard deviation, and image bitmap.similarity measure.  ... 
doi:10.5120/cae-1501 fatcat:tl6irxcvg5dv7n73n5q5kl7e5u

Indexing and Integrating Multiple Features for WWW Images

Heng Tao Shen, Xiaofang Zhou, Bin Cui
2006 World wide web (Bussum)  
And Certainty Factor and Dempster Shafer Theory perform best in combining multiple similarities from corresponding multiple features.  ...  LBS transforms image's text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partition's center.  ...  To retrieve relevant images from large image database, two issues are essential: effectiveness and efficiency. However, most known research results [15] are on retrieval effectiveness.  ... 
doi:10.1007/s11280-006-8560-4 fatcat:abo2roj465gmpjmsp3mgur46fu

The collaborative filtering recommendation based on SOM cluster-indexing CBR

T Roh
2003 Expert systems with applications  
This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference. q  ...  In general, the efforts of improving prediction algorithms and lessening response time are decoupled.  ...  Acknowledgements This research was financially supported by Han Sung University in the year of 2003.  ... 
doi:10.1016/s0957-4174(03)00067-8 fatcat:qq5soh7eazajnpiubbbls35ndu

A Cluster-indexing CBR Model for Collaborative Filtering Recommendation

Tae Hyup Roh, Kyong Joo Oh, Ingoo Han
2003 Pacific Asia Conference on Information Systems  
This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR, with validation against control algorithms through an open dataset of user preference.  ...  In general the efforts of improving prediction algorithms and lessening response time are decoupled.  ...  This study shows that cluster-indexing CBR is an effective user indexing method: The performance of our model yields superior results compared to memory-based CF techniques and other previous hybrid CF  ... 
dblp:conf/pacis/RohOH03 fatcat:7l2fy6wqfzebvdrmzsint2jceq

Clustering User Preferences Using W-kmeans

Christos Bouras, Vassilis Tsogkas
2011 2011 Seventh International Conference on Signal Image Technology & Internet-Based Systems  
We also investigate the effects this approach has on the recommendation engine by evaluating the overall performance it has in terms of precision -recall on our online recommendation system.  ...  We adapt the WordNet-enabled W-kmeans algorithm, an enhancement of standard k-means algorithm which uses the external knowledge from WordNet hypernyms and that has been previously used for document clustering  ...  Investing in knowledge society through the European Social Fund.  ... 
doi:10.1109/sitis.2011.19 dblp:conf/sitis/BourasT11 fatcat:zj2ovrwms5g5nccrqtzh5zzxwy

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

Deok-Hwan KIM
2009 IEICE transactions on information and systems  
The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance  ...  Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based  ...  Region-Based Image Retrieval Most early image retrieval systems represent images by a set of global features such as color, texture, and shape, and they perform retrieval based on similarity in the feature  ... 
doi:10.1587/transinf.e92.d.413 fatcat:3tht73pofbfqhnfremokeheeiy

Automatic machine interactions for content-based image retrieval using a self-organizing tree map architecture

P. Muneesawang, Ling Guan
2002 IEEE Transactions on Neural Networks  
systems, when applied to image retrieval in compressed and uncompressed image databases.  ...  Experimental results show robust and accurate performance by the proposed method, as compared with conventional noninteractive content-based image retrieval (CBIR) systems and user controlled interactive  ...  ACKNOWLEDGMENT The authors would also like to thank all the people who volunteered in the user subjectivity tests for their time and participation.  ... 
doi:10.1109/tnn.2002.1021883 pmid:18244478 fatcat:y6c2rsnhybhsxg35ebifr7cwgi

Clustering for approximate similarity search in high-dimensional spaces

Chen Li, E. Chang, H. Garcia-Molina, G. Wiederhold
2002 IEEE Transactions on Knowledge and Data Engineering  
We analyze the trade-offs involved in clustering and building such an index structure, and present extensive experimental results.  ...  Our scheme is based on finding clusters and, then, building a simple but efficient index for them.  ...  We would like to thank Kingshy Gho and Marco Patella for their assistance to complete the PAC-NN experiments on the M-tree structure.  ... 
doi:10.1109/tkde.2002.1019214 fatcat:tms525oazvcbtisnevqsbdep5u

Automatic Query Image Disambiguation for Content-Based Image Retrieval [article]

Björn Barz, Joachim Denzler
2017 arXiv   pre-print
A novel feedback integration technique is then employed to re-rank the entire database with regard to both the user feedback and the original query.  ...  Query images presented to content-based image retrieval systems often have various different interpretations, making it difficult to identify the search objective pursued by the user.  ...  Acknowledgments This work was supported by the German Research Foundation as part of the priority programme "Volunteered Geographic Information: Interpretation, Visualisation and Social Computing" (SPP  ... 
arXiv:1711.00953v1 fatcat:z4bil3dmczdjzbwism2tgnueya

Measuring search-engine quality and query difficulty: Ranking with target and freestyle

Robert M. Losee, Lee Anne H. Paris
1999 Journal of the American Society for Information Science  
Each query in the CF database is assigned a difficulty number, and these numbers are found to strongly correlate with other measures of retrieval performance such as an E or F value.  ...  Instead of using traditional performance measures such as precision and recall, information retrieval performance may be measured by considering the probability that the search engine is optimal and the  ...  the specialized medical terms found in the CF database.  ... 
doi:10.1002/(sici)1097-4571(1999)50:10<882::aid-asi5>3.0.co;2-6 fatcat:ujy7du24uzg6hnhledpyuqmika

Pruning long documents for distributed information retrieval

Jie Lu, Jamie Callan
2002 Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02  
only minor losses in the accuracy of distributed information retrieval.  ...  Query-based sampling is a method of discovering the contents of a text database by submitting queries to a search engine and observing the documents returned.  ...  Luhn's Keyword-Based Clustering (LUHNM and LUHNS) Luhn's keyword-based clustering measures the importance of a sentence in the document [8] .  ... 
doi:10.1145/584792.584847 dblp:conf/cikm/LuC02 fatcat:jt6jjkckobdotikyuoehqgthoy

Pruning long documents for distributed information retrieval

Jie Lu, Jamie Callan
2002 Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02  
only minor losses in the accuracy of distributed information retrieval.  ...  Query-based sampling is a method of discovering the contents of a text database by submitting queries to a search engine and observing the documents returned.  ...  Luhn's Keyword-Based Clustering (LUHNM and LUHNS) Luhn's keyword-based clustering measures the importance of a sentence in the document [8] .  ... 
doi:10.1145/584845.584847 fatcat:2nylsyl745dytcqjrn6l5dspee

Implementation of Multi-node Clusters in Column Oriented Database using HDFS

P. Naresh
2017 International Journal of Engineering and Applied Computer Science  
is no multi node clusters and totally based on SQL queries.  ...  In this paper, we use the concepts of HBase, which is a column oriented database and it is on the top of HDFS (Hadoop distributed file system) along with multi node clustering which increases the performance  ...  in fixed field files record tables, and it is standard database and data contained in relational databases and spreadsheets.  ... 
doi:10.24032/ijeacs/0206/03 fatcat:uzq6jine3zc3jbhujfvxbgvc74

QoS Based Approach for Web Service Recommendation

Pooja Chame, Swati Deshpande
2016 International Journal Of Engineering And Computer Science  
In this paper we proposed Collaborative Filtering (CF), we propose an innovative CF algorithm for Q-o-S-based web service recommendation. we provide a personalized map for browsing the recommendation results  ...  ., illsuited performance) to the resulting applications.  ...  First, when a user searches net services victimization LoRec, expected QoS values are displayed next to every candidate service, and the one with the most effective expected price are highlighted in the  ... 
doi:10.18535/ijecs/v5i6.32 fatcat:vorpmt7d3bainalf7gxt6e7lhe
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