Informatics Publishing Limited

P. Menaka ¹, D. Thilagavathy ¹

Affiliations
1 Department of Computer Science and Engineering, Adhiyamman College of Engineering, Hosur, Tamil Nadu, IN

Abstract

The Machine Learning (ML) is almost used in any domain of research and now it has become a reliable tool in the medical domain.ML is a tool by which medical field is integrated with the computer based systems to provide more efficient medical care. The main objective of this work is to show what Natural Language Processing (NLP) and Machine Learning (ML) techniques used for representation of information and what classification algorithms are suitable for identifying and classifying relevant medical information in short texts. It is difficult task to identify the informative sentences in fields such as summarization and information extraction. The work and contribution value with this task is helpful in results and in settings for this task in healthcare field. It provides classification of disease, its cure and prevention. It acknowledges the fact that tools capable of identifying reliable information in the medical domain stand as building blocks for a healthcare system that is up-to-date with the latest discoveries. In this research, it focuses on diseases and treatment information, and the relation that exists between these two entities.

Keywords

Machine Learning, Classification, NLP.

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P. Menaka ¹

Affiliations
1 Department of IT, Dr.N.G.P. Arts and Science College, IN

Abstract

Customers prefer to choose products with more features and capabilities initially, but after having worked with a product, they become frustrated or dissatisfied with the usability problems caused by too many features. This phenomenon is called “feature fatigue”. Clearly, customer’s dissatisfaction after use will have a negative effect on company’s long-term revenue, and the inconsistence is a big challenge for firm’s product development. In this paper the methods of usability evaluation and feature fatigue analysis are described.

Keywords

Product Usability, Feature Fatigue Analysis, Methods of Usability Evaluation, Review Mining.

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P. Menaka ¹, K. Thangadurai ²

Affiliations
1 Department of Computer Science, Manaonmaniam Sundaranar University, IN
2 Department of Computer Science, Government Arts College, Karur, IN

Abstract

Customer relation management is a significant feature in the business development which assists for business peoples to get the knowledge about the customer's opinions and can establish the profitable environment. Customer opinions were utilized to enhance the product, so that customer fulfilment and profit will rise desirably. So it is necessary to execute the functional design of customer opinions regarding the products which depends on the time duration. In the earlier work, Customer Knowledge Management (CKM) is established to raise the profit level of industries by tracking the entire regarding the product which is demanded by the customers. Nevertheless, creating and managing the CKM for the huge volume of the customer is a complex task. It results in inaccuracy, if in case it is done manually with less customer information. This issue is rectified in the proposed research methodology by bringing-in the methodology such as Neural Network based Social Customer Relation Management (NN-SCRM). This algorithm is utilized to examine the following factors by gathering the knowledge of the customer review information: "Predict the future, most profitable customers, maintaining quality of product development, customer life time value, identify customers and their products". This is done according to the information of the customer review, which, in turn, obtained from the customers opinions disclosed by their comments regarding the product. This proposed research work is executed and examined in the MATLAB simulation environment from which it is confirmed that the proposed research framework tends to give the best output than the current CKM frameworks.

Keywords

Knowledge Management, Review Analysis, Pre-Processing, Customer Opinions, Profit.

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P. Menaka ¹, K. Geetha ¹

Affiliations
1 Department of Information Technology, Dr. N.G.P. Arts and Science College, IN

Abstract

The popularity of World Wide Web is increasing day by day by allowing peoples to share/ transfer their information to multiple sites. WWW becomes the most popular source for containing most information from the various peoples from different locations. Search engines are most useful tool which enables users to retrieve their required contents from the websites. However retrieval of more related contents for the users would be more difficult task which is resolved by using the web mining concepts. Web mining is nothing but integration of data mining techniques with the WWW to retrieve the most useful information required by the users. There are various methodologies are proposed by different authors to perform web mining in the effective way. In this analysis work, different methodologies proposed by various authors are discussed in terms of their working procedure along with their merits and demerits.

Keywords

Web Mining, Useful Information, Data Mining, World Wide Web, Search Engine.

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