Tuesday, December 13, 2005

Learning Structural metadata information of books

  • Introduction
Structural meta data can be an important component of the metadata of a book in a digital library.
But, adding the structural tags manually is time consuming. Is there a way of doing it automatically? Especially when we have a large annontated data( by annotated i mean example data containing structural meta data) can we learn some how from it and use it to assign the corresponding structural meta data of a given and new page.

  • Some questions to think about:
  1. Is the problem do-able?
  2. How easy / hard is to to do it ?
  4. If yes what kind of assumptions should we be taking?
  5. What kind of results should we expecting.
  6. What is the related work ?
  7. Any machine learning approaches, what other approches exists?
  8. What are their results and observations ?
  9. Should i use the images or the textual content of the book? what are the adv and disadv in each?
  • A Rudimentary Approach:
As a first step, we assume that the structural meta data is whether the page is the first page in the book, index page, preface, cover page, normal page etc etc.
Can i then view this problem of assigning structural meta data problem as a classification problem. Formulation is as follows:
Given large annontated data containing the structural information, I should be able to successfuly learn from it and use it to assign structural information to any given page
with some accuracy.

Convinced to approach the problem as a classification problem, the question stil remains still the image should be used or the textual content. Howver it is not very clear.
Whatever may be the case, the next important phase in approaching the problem is extracting appropriate features. (this has to be done depending on what we want to use ie image or text).
What machine learning techniques to use? The same old famous Neural Networks with n hidden layers?
Still to think..................

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