 Korean is one of the well-known „pro-drop‟ languages. When translating Korean zero object into languages in which objects have to be overtly expressed, the resolution of zero object is crucial. This paper proposes a machine learning method to resolve Korean zero object. We proposed 8 linguistically motivated features for ML (Machine Learning). Our approach has been implemented with WEKA 3.6.1...

The objective of the project is to design and run a system to answer Jeopardy questions, similar to Watson. In the course of a semester, we developed an open source question answering system using the Indri, Lucene, Bing and Google search engines, Apache UIMA, OpenNLP, and Weka among many additional modules. By the end of the semester, we achieved 18% accuracy on Jeopardy questions, and work ha...

This paper presents data mining techniques that can be used to study voting patterns in the United States House of Representatives and shows how the results can be interpreted. We processed the raw data available at http://clerk.house.gov, performed t-weight calculations, an attribute relevance study, association rule mining, and decision tree analysis and present and interpret interesting resu...

Cotton is one of the major crops in India, where 23% cotton gets exported to other countries. The yield depends on crop growth, and it affected by diseases. In this paper, disease classification performed using different machine learning algorithms. For research, leaf image database was used segment images from natural background modified factorization-based active contour method. First, color ...

In this work, popular discretization techniques for continuous features in data sets are surveyed, and a new one based on equal width binning and error minimization is introduced. This discretization technique is implemented for the UCI Machine Learning Repository [7] dataset, Adult database and tested on two classifiers from WEKA tool [6], NaiveBayes and J48. Relative performance changes for t...

This work aims to use sentiment analysis techniques, data mining, text mining and natural language processing to indicate the polarity of texts using support vector machine. Weka software and a movie review database from Internet Movie Database IMDb were used. This work uses preprocessing filters and WRAPPER techniques and Support Vector Machine (SVM) for classification. It presents better resu...

This paper presents an effective implementation of data preprocessing methodology and data mining referring to integrate decision rules as part of manually written expert system (expert knowledge) with models inducted from data. The methods we have used are standard methods for data pre-processing, including techniques for handling missing data, feature construction, transformation and aggregat...

This paper, combined with the characteristics of the early warning about students' grade, represents an optimization algorithm in order to solve the random selection from the initial clustering center of results to cause major influence this volatility defects .It has integrated into the open source WEKA platform. The optimized algorithm not only guarantees the accuracy of the original algorith...

Subspace clustering mines the clusters present in locally relevant subsets of the attributes. In the literature, several approaches have been suggested along with different measures for quality assessment. Pleiades provides the means for easy comparison and evaluation of different subspace clustering approaches, along with several quality measures specific for subspace clustering as well as ext...

In order to analyze the various sectors of the stocks in stock market field, need to use machine learning algorithms to determine the particular sectors of the stocks in intraday trade. In this paper, we compared different types of clustering algorithm with the help of data mining tool WEKA. This paper will demonstrate the strength and accuracy of each algorithm for clustering in terms of perfo...