WKE (Web Knowledge Extraction) Lab.

WKE focuses on developing Web information systems (WIS) for various domain requirements. By integrating systems and modules about web/text mining methods developed in WKE, WIS can be enhanced to advanced intelligent information systems.

Student Trainings | Requirements for WKE Students | Join Us

Research Topics

Balance research methods and pratical coding and problem-solving skills!

Web/Text Data Mining

  • Search Engine (SE): We developed SE modules consisting of, Text Processing (Sentence/Term Segmentation, Tokenization, Keyword Extraction, Novel Phrase Recognition, 5W Keyword Recognition, etc.), Index Engine and Search Engine, that can be optimized based on requirements of information needs and stress test.

  • Text Mining and Information Extraction: Given a website or several domain keywords, WKE is familiar to crawl the hidden/deep web data so that we can efficiently and effectively build domain databases semi-automatically.

  • Data Mining: Association/Classification/Clustering methods are widely used in our advanced WIS applications.

  • Knowledge Based Construction: Based on aforementioned experiences, we can build domain-related Knowledge Tree efficiently and effectively from domain big data and text.

Software Design and Reuse

  • Model Reuse: We design the I3S (Intelligent Internet Information System/Schema) data model and apply to several WIS applications for industrial and government cases.

  • Software Module Reuse: Kernal software modules are incrementally designed and tested in our case studies, so that WIS Apps can be integrated and tested for rapid prototyping.

  • UI Component Reuse: Based on ReactJS, WebUI Components are also developed as reusable parts.


For Students

Student Trainings

  • Coding Skills: In WKE, senior members are the best mentors for fresh members who are rookies in coding. However, we hope fresh members are prepared before asking problems. That is asking Google first and trying to learn how to submit "right" keywords to Google.

  • Learning by Doing: Fresh members of WKE have to code for check points of their or WKE projects. Therefore, you are told to do a small project rather than to study a text book. For example, you are assigned to develop a web crawler (e.g. crawl a dictionary site into your database) with Python; however, in this project you will learn practical experiences about coding HTML/CSS/JS, Python and SQL.

    There are no text books specially for your projects. Therefore, you do not need text books for learning emergent/edging technonogies and specific requirements. All the knowledge is already on the Web.

  • Result of Project or Thesis: WKE members should develop the WIS App for the demonstration of their projects or master thesis. Therefore, WKE built the DNS (wke.csie domain name server) and bought SSL certificate so that students can easily provide Apps based on certificated HTTPS, such as using FB or Google Map APIs. Also, the result must include some experiments to evaluate the performance of applied or proposed data mining methods.

Requirements for WKE Students

  • Enjoy Coding and Thinking! You can get sense of accomplishment from solving bugs, finishing modules or the whole project. And you always think some applications are stupid and can be improved.

  • Lazy to do tedious wroks! So that you prefer to spend much time to write codes for some rediculous or tedious jobs. You hate to do many many copy-and-paste operations for collecting data.

  • Attitude is everything. You are trainned to developed big WIS applications not a toy. Therefore, your project result respones the quality of yourself.

    Every job is a self-portrait of those who did it; autograph your work with quality.

    件件工作,反映自我,凡經我手,必為佳作

  • Learning by Doing for basic coding Skills: You can learn coding by yourself from W3Schools for many basic programming skills, including HTML5/CSS3/JavaScript, Python, SQL, React, etc. Set a shorten goal for your learning, such as developing a personal site, gathering dictionary data, building a database to store daily logs.

  • For Underdraduate Students: If you are seeking the advisor of Project Study (專題指導老師), you must stay in Lab or WFH (Work From Home, not your hometown) during the whole summer vacation.

  • For Graduate Students: If you are not NCNU students, please ask CSIE department office for accommodation in NCNU campus if you don't want to live outside campus. That is you must stay in Lab during the whole summer vacation. If you registered in NCNU at Spring semester (下學期入學), you must have a study plan for WFH, and present the result to WKE members in the beginning of the Spring semester.

  • Note: WKE members are payed according to their performance. The salary is depenend on current projects.

Join Us

If you are interesting in WKE:

  1. Read this page information seriously.

  2. Evaluate your attitude about "coding things best rather than ok".

  3. E-mail to me with information about yourself.

  4. Then, I will reply the interview schedule to you.


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