Chinese text retrieval without using a dictionary
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
Structural extraction from visual layout of documents
Proceedings of the eleventh international conference on Information and knowledge management
IEEE Transactions on Knowledge and Data Engineering
Data-Driven Discovery of Quantitative Rules in Relational Databases
IEEE Transactions on Knowledge and Data Engineering
Data extraction and label assignment for web databases
WWW '03 Proceedings of the 12th international conference on World Wide Web
Applying Machine Learning to Text Segmentation for Information Retrieval
Information Retrieval
Web data extraction based on partial tree alignment
WWW '05 Proceedings of the 14th international conference on World Wide Web
Using visual cues for extraction of tabular data from arbitrary HTML documents
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Automatic extraction of table metadata from digital documents
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
A hybrid named entity recognizer for Turkish
Expert Systems with Applications: An International Journal
Decision support for foreign investment strategy under hybrid uncertainty
Expert Systems with Applications: An International Journal
Geographic knowledge discovery from Web Map segmentation through generalized Voronoi diagrams
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
Due to an increase in the wealth of electronic resources on the Internet in the past several years, the birth of the search engine has brought the utmost convenience and efficiency for users. However, searching for data by keyword retrieval techniques in information retrieval is not contented with some users' specific needs due to a large number of network resources and users on the Internet. Information extraction is an improvement method which extracts the important specific event or produces specific relations among information from documents. Information extraction can not only filter unnecessary information in any documents but also produce specific important messages and summaries that users are interested in. Business valuation is collecting, analysis, and applying to financial or non-financial integral information to appraise the business value. The evaluated results are used in the commerce pricing for the business decision and intangible assets. There are specific information and events about business valuation stored in the Intelligent financial statements, notes to financial statements, and financial news of Taiwan's companies at present and data is presented by the HTML and PDF files. Hence, we developed an information extraction system of Chinese financial data for business valuation from the domestic business financial statements, notes to financial statements, and financial news as the data sources. We extracted the correct financial data and their corresponding Business Valuation Model to achieve an automatic extraction in the financial data from these different heterogeneous data sources. Users can collect the relevant valid valuation information and learn valuation models concepts within a very short time to improve accuracy and efficiency in text processing quality.