1 / 51

Random Thought on Research Methods in CS/CIS

Delve into the realm of research methods in Computer Science and Information Systems, understanding the significance, techniques, and applications while broadening your horizons to new discoveries and solutions.

topping
Download Presentation

Random Thought on Research Methods in CS/CIS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Random Thought on Research Methodsin CS/CIS CSCI 6530 July 1, 2010 Kwok-Bun Yue University of Houston-Clear Lake

  2. Random • Random: not organized. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  3. Merriam-Webster • Research • 1 : careful or diligent search • 2 : studious inquiry or examination; especially : investigation or experimentation aimed at the discovery and interpretation of facts, revision of accepted theories or laws in the light of new facts, or practical application of such new or revised theories or laws • 3 : the collecting of information about a particular subject Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  4. For what? • Finding new things: facts, theories, processes, tools, relationships, techniques. • Solving problems Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  5. Why Research? • Solving problems. • Enhancing understanding. • Career enhancement. • Curiosity and fun. • … Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  6. Research Methods • Discipline dependent. • E.g. medical research: double blind test with control. • Scientific methods. • Empirical methods. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  7. Starting Research • What do you need to start your research? • Talk! Talk! Talk! • Think! Think! Think! • Read! Read! Read! Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  8. Asking Questions • ASK! ASK! ASK! Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  9. Not Asking Questions • Easy • Comfortable • Familiar • … Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  10. Asking is crucial • Get a context of the problem from many angles. • Organize your thought. • Model and refine your understanding. • Discover new information and insight. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  11. Intellectual Curiosity • A key for deep understanding, important discovery and … fun. • Sometimes not too output driven: need of ‘down’ time. • Recommended reading: Surely You're Joking, Mr. Feynman! (Adventures of a Curious Character) by Richard Feynman. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  12. Keeping an open mind • Keep an open mind as long as possible. • Do not jump to the first solution that you have come up with. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  13. Research in Physics • Scientific Methods: • Observe, ask questions and understand • Make hypothesis and model • Make (precise) predictions using the hypothesis. • Test the predictions. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  14. Questions in Physics • Fundamental questions: e.g. • Can the four fundamental forces be unified: theory of everything? • Where do our universe come back? • What are elementary particles make of? Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  15. Results in Physics • Theories: e.g. • Superstring theory. • Big bang theory • Quarks • New facts. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  16. Validations in Physics • Experiment with predictions by theories. • E.g.: Big bang theory predicts abundance of light elements. • Positive results: add confidence. • Negative results: reject theory. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  17. Questions in Computing • Much more diverse. Have aspects from most other areas: engineering, science, humanities, … • Can create your own ‘universe’. (vs economic, for example) Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  18. Result in CS • New theories, algorithms, processes, methods, facts, etc. • New models, problems and application areas. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  19. Validations • Direct validation • Theoretical analysis • Simulation • Benchmarking • Statistical methods • … Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  20. Planning: Goals • Output oriented incentives can be too ‘far away’. • Setting plans and goals. • Create a detail plan of steps and benchmarks. • Small goals every step. • Consider input-oriented goals. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  21. Early Web Business Model Build Websites Attract Huge Traffic Something happens Rich! Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  22. Thesis Understand Problem Design and Implement Solution Good thing happens Done! Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  23. Detailed Plan • Create a road map with enough details to the final goals. • Preparation. • Planning • Risk Management • Recommended reading: Ed Viesturs, “No Shortcuts to the Top: Climbing the World's 14 Highest Peaks” Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  24. Areas of My Research Interest • Internet Computing • XML and semi-structured data • CS and IS education • Concurrent Programming Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  25. (Older) XML Projects • Storage of XML in relational database (Used as an example) • XML Metrics Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  26. Storing XML in RDB • Advantages: • Mature database technologies. • May be queried by • XML technology: e.g. XPath, XQuery. • RDB technology: e.g. SQL. • Disadvantages: • impedance mismatch: XML and relations are different data models. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  27. Related Issues • Effective mapping XML DTDs (~ ordered tree model) to relational schemas. • Mapping of XML queries (e.g. XQuery) to RDB queries (e.g. SQL). • Mapping of RDB query results back to XML format. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  28. Related Work and Context • Mapping • With or without schemas for XML. • With or without user input. • Schemas for XML: • Document Type Definition (DTD) • XML Schema • We consider mapping with DTD and without user input. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  29. Naïve Mapping • An XML element is mapped to a relation. Example 1a: XML: <a><b><c><d>hello</d></c></b></a> -> Relations: a, b, c and d. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  30. Problems of Naïve Mapping • Many relations. • Ineffective queries: multiple query joins. Example 1b: XPath Query: //a SQL Query: need to join the relations a, b, c and d. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  31. Inlining Algorithms • First proposed by Shanmugasundaram, et. al. • Expanded by Lu, Lee, Chu and others. • Extended in various directions by various researchers, e.g., • Preserving XML element orders. • Preserving XML constraints. • Do not consider extensions here. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  32. Basic Idea of Inlining Algorithms • Inline child element into the relation for the parent element when appropriate. • Different inlining algorithms differ in inlining criteria. Example 1c: XML: <a><b><c><d>hello</d></c></b></a> Inlined Relation: a. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  33. Inlining Algorithms • Child elements & attributes may be inlined. • Child elements may not have their own relations. • Results in less number of relations. • In general, more inlining -> less joins. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  34. Inlining Algorithm Structure • Simplification of DTD. • Generation of DTD graphs • Generation of Relational Schemas Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  35. Our work • Improved on simplification of DTD and generation of DTD graphs. • Constructed a new aggressive inlining algorithm. • Student: Alakappan. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  36. Internet Computing • Web bias (older project) • Web 2.0 framework (IS project) • Content Management Software (CMS): Joomla (CS/IS Education) • Mashup: Yahoo Pipe (CS/IS Education) Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  37. Measuring Web Bias • Search engines dominate how information are accessed. • Search results have major social, political and commercial consequences. • Are search engines biased? • How bias are them? Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  38. Previous Works • To measure bias, results should be compared to a norm. • The norm may be from human experts. • Mowshowitz and Kawaguchi: the average search result of a collection of popular search engines as the norm. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  39. Mowshowitz and Kawaguchi Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  40. Limitations • Based on URL Vector -> cannot measure bias quality. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  41. Our Approach • Use Kleinberg’s HITS algorithm to create clusters, authorities and hubs of the result norm URLs. • Use them as norm clusters, authorities and hubs. • Measure distances between norms and individual results as bias. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  42. Our Approach Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  43. Recent Projects • Web 2.0 framework: • A model and framework to study Web 2.0 technologies, implications and trends. • Collaborator: Mr. Tracy Gate. • Publications: Pre-ICIS Workshop and Communications of AIS. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  44. CMS: Joomla • Question: Using CMS/Joomla for capstone project. • Methodology: projects and surveys. • Collaborator: • Capstone project teams. • Industrial mentor: Dilhar DeSilva • Publication: Journal of Information Systems Education. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  45. End User Programming • Use of Yahoo/Pipeline in constructing Web Mashup. • Methodology: projects and surveys. • Collaborators: students in the XML class in Summer 2009. • Publication: Journal of Information Systems Education. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  46. Ongoing projects • Googlewave as communications/collaboration tools in capstone projects and software project management. • Collaborators: capstone project students. • Publications: under preparation. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  47. Open Source Software • Use of OSS in educational institutes. • Methodology: meta-analysis. • Collaborators: two master students. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  48. Other recent projects • Assessment • Scholarship • Student Response Systems Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  49. Interested? • Come and talk with me. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

  50. Conclusions • Good time to do applied computing research in the Web, XML and other areas. • Style: hands-on supervision + publications. • Don't forget to donate a scholarship to the School if your future research leads to a windfall. Bun Yue: yue@uhcl.edu, http://dcm.uhcl.edu/yue

More Related