| Paper title: |
Application for Suggesting Restaurants Using Clustering Algorithms |
| Published in: | Issue 3, (Vol. 8) / 2014 |
| Publishing date: | 2014-10-30 |
| Pages: | 26-30 |
| Author(s): | IANCU Iulia Alexandra, IANCU Eugenia |
| Abstract. | The aim of this article is to present an application whose purpose is to make suggestions of restaurants to users. The application uses as input the descriptions of restaurants, reviews, user reviews available on the specialized Internet sites and blogs. In the application there are used processing techniques of natural language implemented using parsers, clustering algorithms and techniques for data collection from the Internet through web crawlers. |
| Keywords: | Web Crawler, Parser, Stemmatizer, Cluster, Lemmatizer, Data Mining, Machine Learning. |
| References: | 1. MacQueen, J. B. (1967). "Some Methods for classification and Analysis of Multivariate Observations". Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability 1. University of California Press. pp. 281–297 2. MacKay, David (2003). "Chapter 20. An Example Inference Task: Clustering". Information Theory, Inference and Learning Algorithms. Cambridge University Press. pp. 284–292 3. Rajaraman, A.; Ullman, J. D. (2011). "Data Mining". Mining of Massive Datasets. pp. 1–17 4. Salton G; McGill MJ (1986). Introduction to modern information retrieval. McGraw-Hill. ISBN 0-07-054484-0. 5. Wu HC, Luk RWP, Wong KF, Kwok KL (2008). "Interpreting tf–idf term weights as making relevance decisions". ACM Transactions on Information Systems 6. Manning, C. D.; Raghavan, P.; Schutze, H. (2008). "Scoring, term weighting, and the vector space model". Introduction to Information Retrieval. p. 100 |
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