"Profile of Industrial workers in Kerala - A Comparative Study of the Socioeconomic Profile of Workers in Traditional and Modern Industries

The objective of this study is to assess the changes that have been taking place in the socio-economic profile of organized industrial workers of Kerala in the context of the changes that have been taking place in the state's industrial structure. with this object in view, the study seeks to find out the similarities and differences in the profile of workers belonging to two Segments of factory sector industries in Kerala viz., modern and traditional segments. It also seeks to examine the factors leading to the differences in profile, if any, and their consequences. As noted earlier, the profile of workers may be influenced both by external societal factors and by internal factors like the difference in industrial structure and the technologies used. It is proposed to assess the relative importance of these two groups of factors. In drawing up the profile, we seek to find out whether the workers belonging to the organised sector of industry in Kerala particularly the more modern sector have begun to form a ‘select group‘ in the Kerala society and the total work force. Wherever possible, it is proposed to compare the profile of the Kerala workers with those of workers in other states of India. As an incidental objective, it is also proposed to find out to the extent possible, whether trends towards labour embourgeoisement and class shifting have begun to set in among the industrial workers of Kerala, particularly among the workers in the modern industries as a result of their relative affluence and their middle class socioeconomic background. besides, the study seeks to find out whether there is any difference in the class consciousness of workers belonging to these two segments of organized industry, arising from the differences in their economic status and social background.

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements