Given the paramount importance of data mining in organizations and possible contribution a data-driven customer classification recommender systems for loan-extending financial institutions, study applied supervised approaches to derive best classifier loan default. A total 900 instances with determined attributes class labels were used training cross-validation processes while prediction 100 ne...

Named entity linking (NEL) grounds entity mentions to their corresponding Wikipedia article. State-of-the-art supervised NEL systems use features over the rich Wikipedia document and link-graph structure. Graph-based measures have been effective over WordNet for word sense disambiguation (WSD). We draw parallels between NEL and WSD, motivating our unsupervised NEL approach that exploits the Wik...

Paintings which was handled roughly or made from low quality paint or base usually suffers from crack in a long run, which causes them to lose some of the information. This paper discuss about automatic approach for classification and interpolation of cracks. For classification supervised and unsupervised methods were implemented and for interpolation different order statistics filter were appl...

This paper presents a comparative account of unsupervised and supervised learning models and their pattern classification evaluations as applied to the higher education scenario. Classification plays a vital role in machine based learning algorithms and in the present study, we found that, though the error back-propagation learning algorithm as provided by supervised learning model is very effi...

This report gives a brief introduction of our participation in CL-SciSumm 2017 Task 1A. We demonstrate some data analysis and point out the difficulty of this task. Then we report both unsupervised and supervised methods with their performances on 2016 and 2017 testset, from which efficiency of different features can be estimated.

Remote sensing of lake water quality assumes there is no universal method or algorithm that can be applied in a general way on all inland waters, which usually have different in-water components affecting their optical properties. Depending the place and time year, dynamics, particular water, non-tailor-designed algorithms lead to large errors lags quantification parameters, such as suspended m...

We present an automatic method for senselabeling of text in an unsupervised manner. The method makes use of distributionally similar words to derive an automatically labeled training set, which is then used to train a standard supervised classifier for distinguishing word senses. Experimental results on the Senseval-2 and Senseval-3 datasets show that our approach yields significant improvement...

Classification task involves inducing a predictive model using a set of labeled samples. The more the labeled samples are, the better the model is. When one has only a few samples, the obtained model tends to offer poor result. Even when labeled samples are difficult to get, a lot of unlabeled samples are generally available on which unsupervised learning can be used. In this paper, a way to co...

This paper proposes an unsupervised learning framework in which models of objects’ appearance classes are learned using their spatio and temporal information, from video. These models are used to detect objects of different classes in the everyday scene. The proposed technique combines appearance and motion features in a weighted combination framework resulting in models of object classes. Thus...