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Duong, T. V. T., Do, T. D., & Nguyen, N. P. (2015, July). Exploiting faculty evaluation forms to improve teaching quality: An analytical review. In Science and Information Conference (SAI), 2015 (pp. 457-462). IEEE. |
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2 |
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Lim, J. H., & Lee, K. C. (2015). Classifying Biomedical Literature Providing Protein Function Evidence. ETRI Journal, 37(4), 813-823. |
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Barros, V. F. D. A., Ramos, I., & Perez, G. (2015). information systems and organizational memory: a literature review. JISTEM-Journal of Information Systems and Technology Management, 12(1), 45-63. |
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4 |
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Redding, L. (2015). Through-Life Engineering Services: Definition and Scope: A Perspective from the Literature. In Through-life Engineering Services (pp. 13-28). Springer International Publishing. |
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Redding, L. E., Hockley, C. J., Roy, R., & Menhen, J. (2015). The Role of Maintenance, Repair, and Overhaul (MRO) Knowledge in Facilitating Service Led Design: A Nozzle Guide Vane Case Study. In 9th WCEAM Research Papers (pp. 379-395). Springer International Publishing. |
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Asayesh, A., Hadavi, M. A., & Jalili, R. (2015). (t, k)-Hypergraph anonymization: an approach for secure data publishing. Security and Communication Networks, 8(7), 1306-1317. |
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7 |
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Rupnik, J., Davies, J., Fortuna, B., Duke, A., & Clarke, S. S. (2015, October). Travel Time Prediction on Highways. In Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM), 2015 IEEE International Conference on (pp. 1435-1442). |
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Hung, L. N., Thu, T. N. T., & Nguyen, G. C. (2015). An Efficient Algorithm in Mining Frequent Itemsets with Weights over Data Stream Using Tree Data Structure. International Journal of Intelligent Systems and Applications (IJISA), 7(12), 23. |
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9 |
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Brar, S., Mathur, D., Sharma, N., & Phagwara, P. Enhancement in Semantic based Model for Text Document Clustering. |
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Shyamala, V. S., & Christopher, T. (2015). Managing Privacy of Sensitive Attributes Using MFSARNN Clustering with Optimization Technique. International Review on Computers and Software (IRECOS), 10(9), 907-911. |
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Parlak, B., & Uysal, A. K. (2015, May). Classification of medical documents according to diseases. In Signal Processing and Communications Applications Conference (SIU), 2015 23th (pp. 1635-1638). IEEE. |
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12 |
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Shah, P. R., Vaghela, D. B., & Sharma, P. (2015, March). Faculty performance evaluation based on prediction in distributed data mining. In Engineering and Technology (ICETECH), 2015 IEEE International Conference on (pp. 1-5). IEEE. |
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13 |
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Kalibataite, G. (2014). Integration of activity data: problems, peculiarities and the importance of metadata. Socialines Technologijos, 4(1). |
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14 |
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Kalibataite, G. (2014). Veiklos duomenu integravimas: problemos, ypatumai ir metaduomenu svarba. Social Technologies, (01), 93-117. |
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15 |
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Drakshayania, B., & Prasad, E. V. Hybrid Clustering Model for Text Documents with Semantic Based Document Representation. |
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16 |
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Shaari, F., Ahmad, A., & ALong, Z. (2014). Outlier Detection Method based on Hybrid Rough-Negative Algorithm. Journal of Mathematics and System Science, 4(6). |
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17 |
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Suguna, N. (2014). Certain investigations on Classification of medical datasets Using soft computing techniques. |
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18 |
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Kanakam, P., Gupta, S., Hussain, S. M., & Narayana, D. S. (2014). An Analysis of Exploring Information from Search Engines in Semantic Manner. International Journal, 4(5). |
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Tâmbulea, l., darabant, a. s., & varga, v. (2014). data transfer optimization in distributed database query processing. studia universitatis babes-bolyai, informatica, 59(1). |
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20 |
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Long, A. (2014) Outlier Detection Method based on Hybrid Rough-Negative Algorithm Mathematics and Systems Science: English, 4 (6), 391-397. |
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21 |
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Kotulla, A. (2012). Negative associacion rules–computing, measures and application areas. Studia Informatica, 33(2B), 273-285. |
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Ahmad, A., Shaari, F., & Long, Z. A. (2014, January). Outlier detection method based on hybrid rough: negative using PSO algorithm. In Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication (p. 108). ACM. |
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23 |
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Khan, I. A., & Choi, J. T. (2014). An Application of Educational Data Mining (EDM) Technique for Scholarship Prediction. International Journal of Software Engineering and Its Applications, 8(12), 31-42. |
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24 |
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Singh, A. K., Tondon, S. R., & Diwan, T. D. One Time Mining by Multi-Core Preprocessing on Generalized Dataset. |
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25 |
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Sharma, S. K., & Ugrasen, S. (2014). A trust-based architectural framework for collaborative filtering recommender system. International Journal of Business Information Systems, 16(2), 134-153. |
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Devi, M. K., & Rani, M. U. Fuzzy Weighted Associative Classifier based on Positive and Negative Rules. |
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27 |
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Mala, A., & Ramesh, D. F. (2014, August). Web Log Mining to Enhance Surfing Experience. In Applied Mechanics and Materials (Vol. 626, pp. 7-13). Trans Tech Publications. |
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28 |
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binti Dollah, R., & Aono, M. (2014). Employing Ontology Enrichment Algorithm in Classifying Biomedical Text Abstracts. |
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29 |
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Mathai, P. P., & Balan, R. S. An Extensive Review of Significant Researches in Data Mining. |
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30 |
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Drakshayani, B., & Prasad, E. V. (2013). Semantic Based Model for Text Document Clustering with Idioms. Intl. J. Date Engg, 4(1), 1-13. |
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31 |
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Nguyen, T. T., & Nguyen, P. K. (2013). A New Viewpoint for Mining Frequent Patterns. Editorial Preface, 4(3). |
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32 |
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Roongkaew, W., & Prompoon, N. (2013, September). Software engineering tools classification based on SWEBOK taxonomy and software profile. In Informatics and Applications (ICIA), 2013 Second International Conference on (pp. 122-128). IEEE. |
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33 |
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Sharma, S. K., & Suman, U. (2013). A framework of hybrid recommender system for web personalisation. International Journal of Business Information Systems, 13(3), 284-316. |
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34 |
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Sharma, S. K., & Suman, U. (2013). An efficient semantic clustering of URLs for web page recommendation. International Journal of Data Analysis Techniques and Strategies, 5(4), 339-358. |
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35 |
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Ali, S. Z., & Rathore, Y. A comprehensive study of major techniques of multi level frequent pattern mining: a survey. |
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36 |
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Tahir, d. n. international journal of data engineering (ijde). |
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37 |
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Bangalore, M. H. S. (2012). Resource adaptive technique for frequent itemset mining in transactional data streams. IJCSNS, 12(10), 87. |
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38 |
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Drakshayani, B., & Prasad, E. V. Metaphor based Document Representation Model for Text Document Clustering. In IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (pp. 74-78). |
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39 |
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Aher, S., & Lobo, L. M. R. J. (2012). Mining association rule in classified data for course recommender system in e-learning. International Journal of Computer Applications, 39(7), 1-7. |
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40 |
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Kotulla, A. (2012). Negatywne reguly asocjacyjne-wyznaczanie, miary i obszary zastosowania. Studia Informatica, 33(2B), 273-285. |
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41 |
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Li Haifeng, Zhang Ning, Zhu Jianming, & Caohuai Hu. (2012) itemsets time-sensitive data stream mining algorithms. Journal of Computers, 35 (11), 2283-2293. |
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42 |
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Nguyen, T. T., & Nguyen, P. K. (2012). A new approach for problem of sequential pattern mining. In Computational Collective Intelligence. Technologies and Applications (pp. 51-60). Springer Berlin Heidelberg. |
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43 |
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Chandrika, J., & Kumar, K. A. (2012). Frequent Itemset Mining in Transactional Data Streams Based on Quality Control and Resource Adaptation. International Journal of Data Mining & Knowledge Management Process, 2(6), 1. |
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44 |
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Suneetha, s., & rani, m. u. status quo of semantic-based text document clustering: a review. |
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45 |
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Patil, g. y., shahade, a. k., & bamnote, d. g. r. (2012). international journal of pure and applied research in engineering and technology. ret, 1(1), 1-7. |
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46 |
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B Aher, S., & LMRJ, L. (2012). Combination of clustering, classification & association rule based approach for course recommender system in E-learning. International Journal of Computer Applications, 39(7), 8-15. |
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47 |
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Verma, G., & Nanda, V. (2012). Frequent Item set Generation by Parallel Preprocessing on Generalized Dataset. International Journal of Scientific & Engineering Research, 3(4). |
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48 |
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Sharma, S. K., & Suman, U. (2012, September). Comparative study and analysis of web personalization frameworks of recommender systems for e-commerce. In Proceedings of the CUBE International Information Technology Conference (pp. 629-634). ACM. |
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49 |
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Verma, G., & Nanda, V. (2012). Association Rule Mining by Block Scattered Transposition. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 1(3), pp-99. |
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50 |
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Nguyen, Q. D. (2012). The role of business intelligence in organizational memory supporti. |
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51 |
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Rölker-Denker, L., & Hein, A. (2012). Organisationales Lernen und Organisationale Gedächtnisse im AAL-Kontext. Technik für ein selbstbestimmtes Leben. |
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52 |
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Herawan, T., Noraziah, A., Abdullah, Z., Deris, M. M., & Abawajy, J. H. (2012). EFP-M2: efficient model for mining frequent patterns in transactional database. In Computational Collective Intelligence. Technologies and Applications (pp. 29-38). Springer Berlin Heidelberg. |
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53 |
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Diwakar, S., Singhai, R., & Thakur, N. S. power constant based methods for dealing with missing values in knowledge discovery. |
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54 |
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Verma, G., & Nanda, V. (2012, March). An Effectual Algorithm For Frequent Itemset Generation In Generalized Data Set Using Parallel Mesh Transposition. In Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on (pp. 719-724). IEEE. |
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55 |
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Aher, S. B., & Lobo, L. M. R. (2012). Best combination of machine learning algorithms for course recommendation system in e-learning. International Journal of Computer Applications, 41(6). |
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56 |
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SU, Y. R., WANG, R. J., Peng, C. H. E. N., WEI, Y. Y., LI, C. X., & HU, Y. M. (2012). Agricultural ontology based feature optimization for agricultural text clustering. Journal of Integrative Agriculture, 11(5), 752-759. |
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57 |
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Kuo, C. C., & Shieh, H. L. (2012). A Semi-Supervised Learning Algorithm for Data Classification. International Journal of Pattern Recognition and Artificial Intelligence, 1551007. |
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58 |
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Abbas, M., & Shoukry, A. (2012, July). CMUNE: A clustering using mutual nearest neighbors algorithm. In Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on (pp. 1192-1197). IEEE. |
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Shukla, D., Verma, K., & Gangele, S. re-attempt connectivety to internet analysis of user by markov chain model. chief patron chief patron. |
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Sharma, S. K., & Suman, U. (2011). Analysis of Frequent URLs for a Recommender System Using Performance Based Transposition Algorithm. Automation and Autonomous System, 3(11), 526-532. |
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Sharma, S. K., & Suman, U. (2011). Design and Implementation of Architectural Framework of Recommender System for e-Commerce. International Journal of Computer Science and Information Technology & Security (IJCSITS), 1(2), 153-162. |
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Gangele, S., Shukla, D., Verma, K., & Singh, P. (2011). Elasticities and Index Analysis of Usual Internet Traffic Share Problem. International Journal of Advanced Research in Computer Science, 2(4). |
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Shukla, D., Singhai, R., & Thakur, N. S. (2011). A New Imputation Method for Missing Attribute Values in Data Mining. Journal of Applied Computer Science & Mathematics, (10). |
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Liukkonen, M. (2010). Intelligent Methods in the Electronics Industry. University of Eastern Finland. |
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65 |
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El-Yazeed, N. A. A Survey on Web Recommendation Systems Based on Web Usage Mining. |
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66 |
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Liu, L., Wang, Y., & Liu, S. (2013). Model of opinion interactions base on evolutionary game in social network. In Intelligent Computing Theories and Technology (pp. 64-72). Springer Berlin Heidelberg. |
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67 |
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Bajaj, P., & Raheja, S. (2014). A Vague Improved Markov Model Approach for Web Page Prediction. arXiv preprint arXiv:1405.7868. |
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Thwe, P. Using Markov Model and Popularity and Similarity-based Page Rank Algorithm for Web Page Access Prediction. |
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Liua, L., Lvb, J., Lic, J., & Wangc, Y. Evolutionary Game Model of Information Interaction in Social Network?. |
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