Text Mining Using Metadata for Generation of Side Information

“…In metadata based text mining, huge web online collection is the main reason to develop a mechanism to create effective and scalable clustering algorithms used for generating side information [1][2][3]. The current proposed approaches focus on data processing to maximize the clustering advantage to generate side information.…”

Section: Related Workmentioning

confidence: 99%

“…It provides an idea to perform mining process a way to perform the mining process as to maximize the benefits of side information. It uses an algorithm which is a combination of traditional partitioning algorithms with the probabilistic models [1]. The stemming is the process in mining, to reduce different grammatical or word forms of a word like its noun, adjective, verb, adverb etc.…”

Section: Related Workmentioning

confidence: 99%

“…How to analyze the knowledge from unstructured texts [1][2] is the main research component present in text mining called as text data mining (TDM) [3][4]. The process of text mining is similar to data mining process; difference is that the data mining tools are used to handle structured data whereas text mining tools are used to handle unstructured data sets ex.…”

Section: Introductionmentioning

confidence: 99%

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Metadata based Text Mining for Generation of Side Information

Bhanuse¹,

Kamble²,

Thakur³

et al. 2017

Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering

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Abstract-Text mining is knowledge analyzing technique to find a pattern. The side information is also called as metadata in most of the metadata based text mining applications. The side information consisting of large data in terms of weblogs, metadata, and non-textual data i.e. image/video, etc. This large data present in the unprocessed form which cannot be used for further text mining. Therefore, metadata based text mining algorithms are used to mine the useful information. In this paper, the proposed approach uses the different kind of pre-processing steps i.e. splitting, tokenize, steaming, parsing and chunking. For generating the side information i.e. title, name, affiliation, email address, place etc. a natural language processing (NLP) is used. To achieve the effective clustering, the proposed approach uses a classical partitioning method with a probabilistic model. The proposed approach is compared in terms of time required for mining of words, accuracy, and efficiency. The presented result shows that, the proposed approach performs better in terms of accuracy and running time. In future, a Security is provided for metadata based side information generation using Intrusion Detection System (IDS).

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“…In this text, mining research is used to reduce unnecessary words so that the text, the user can understand with secure information on the text [13], [7]. The workings of the system to be built are the elderly photographing announcements available at hospitals, puskesmas, and clinics.…”

Section: Introductionmentioning

confidence: 99%

Implementation of TF-IDF Algorithm to detect Human Eye Factors Affecting the Health Service System

Sudarma

Sulaksono²

2020

intensif

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Elderly is someone whose age is around 60-74 years, at that age, one's health tends to decrease, and it has an impact on reduced perception, cognition, and psychometry. One result of cognitive decline is a decrease in memory. Programs have been provided by the Indonesian government, such as submitting information, producing brochures, and making announcements on the health services website. But this counseling is not optimal because the elderly tend to be lazy to read this because the eyes have begun to look away from other than that the eye health of the elderly has already started to decrease. So that the health information provided by the health department can be optimized, we try to make a model that is used to summarize an article so that the article is easily understood by the elderly. To summarize the article, this study uses the term frequency-inverse document frequency (TF-IDF) algorithm. By using the TF-IDF algorithm, it is hoped that the elderly will more easily read health articles. User Experience Questionnaire after the application of writing software summary is higher than before the application of writing software summary that is 25.27> 19.30.

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Text Mining Using Metadata for Generation of Side Information

Cited by 16 publications

References 24 publications

Designing a model of a decision support system based on a multi-aspect factographic search

Designing a model of a decision support system based on a multi-aspect factographic search

Metadata based Text Mining for Generation of Side Information

Implementation of TF-IDF Algorithm to detect Human Eye Factors Affecting the Health Service System

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