Biomedical literatures have been increased at the exponential rate. To find the useful and needed information from such a huge data set is a daunting task for users. Text mining is a powerful tool to solve this problem. In this paper, we surveyed on text mining in Bioinformatics with emphasis on applications of text mining for bioinformatics. In this paper, the main research directions of text mining in bioinformatics are accompanied with detailed examples. This paper suited the need for the state-of-the-art of the field of text mining in Bioinformatics because of the rapid development in both text mining and bioinformatics. Finally, the problems and future way are identified at last.
Medical text mining has gained increasing interest in recent years. Radiology reports contain rich information describing radiologistpsilas observations on the patientpsilas medical conditions in the associated medical images. However, as most reports are in free text format, the valuable information contained in those reports cannot be easily accessed and used, unless proper text mining has been applied. In this paper, we propose a text mining system to extract and use the information in radiology reports. The system consists of three main modules: a medical finding extractor, a report and image retriever, and a text-assisted image feature extractor. In evaluation, the overall precision and recall for medical finding extraction are 95.5% and 87.9% respectively, and for all modifiers of the medical findings 88.2% and 82.8% respectively. The overall result of report and image retrieval module and text-assisted image feature extraction module is satisfactory to radiologists.
Research and Implement of Classification Algorithm on Web Text Mining
ABSTRACT
Research and application of Web text mining is an important branch in the data mining. Web is the biggest information system currently. Now people mainly use the search engine to look up Web information. The problem of getting reliable rate and comprehensive rate is increasingly convex, and it is very difficult to mine data further. Now the search engine can hardly provide individual service according to different need of different customers. However, Web text mining aims at resolving this problem. This paper discusses an Algorithm of how to follow the appointed Website or Web page according to the user's request, how to analysis, compare, sample, reserve and classify the data information combined with the Web page text contents for later use. The model of Web text mining, mining algorithm and implement technique are discussed in details.
A Novel Web Text Mining Method Based on Semantic Polarity Analysis
ABSTRACT
The purpose of Web text mining is to find the potential knowledge from the immensity text information on the Internet. In this paper, a novel Web text mining method is proposed based on semantic polarity analysis. Firstly, the model for Web text mining is presented by using semantic polarity analysis, which includes three main parts: data acquisition, feature sentences analysis and semantic polarity analysis. Secondly, the procedure with semantic polarity analysis is introduced for Web text mining, and the related algorithms are also discussed. Thirdly, the method is applied into an actual case to try to find out the valuable products information for the consumers. The results show that the method is both reasonable and effective.
This study proposes a novel Web-based text mining (WTM) framework on the grid, which firstly applies the grid technology to text mining system for improving the performance of WTM. The WTM system is to implement a high performance text mining process on the grid, and provide users with a high efficiency text mining and knowledge discovery services. We focus our discussion on the formulation of this framework for WTM system on the grid. In this study, firstly, a general framework of grid-based WTM is proposed, then a main process about WTM on the grid is described, and subsequently the implementation of the proposed grid-based WTM framework model is given. Finally, some conclusions are given.
Research and Realization of Text Mining Algorithm on Web
ABSTRACT
It is recognized that text information on Web is growing at an astounding pace. Research and application of text mining on Web is an important branch in the data mining. Now people mainly use information retrieval (IR) or the search engine to look up Web information. But IR focuses on searching for information that is explicitly present but not latent knowledge in some document, the search engine can hardly according to different need of different customers and provide individual service, and it is very difficult to mine data further. However, text mining on Web aims to resolve this problem. This paper discusses an Algorithm of how to follow the appointed website or Web page according to the user's request by using the text mining technique, how to extract and express text characteristic, how to classify the data information with feedback judgement combined with the Web page text contents for later use. We present experiments on different data set that demonstrate more effectiveness of our algorithm than traditional algorithm. The process of Web text mining, information extraction method, mining algorithm and realization technique are discussed in details.