Teadmised first lab 2011: erinevus redaktsioonide vahel

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The main goal of the first lab is to web-scrape data from the public sources using search engines and simple text analysis/statistics.  
The main goal of the first lab is to web-scrape data from the public sources using search engines and simple text analysis/statistics.  
== Conditions ==
You can do the lab either alone or together with a fellow student. Three students per lab is not ok, though.
Technology - language, op system etc - is completely free.
== What should the app do ==


Your system should take as input a list of arbitrary investigated objects like "Tower Bridge", "Statue of Liberty", "Tallinna raekoda", "Olde hansa", "Tallinn University of Technology", "Andrus Ansip", "Ford focus", "inception" and use web search and web-scraping to obtain probabilistic data about the objects. We look for  
Your system should take as input a list of arbitrary investigated objects like "Tower Bridge", "Statue of Liberty", "Tallinna raekoda", "Olde hansa", "Tallinn University of Technology", "Andrus Ansip", "Ford focus", "inception" and use web search and web-scraping to obtain probabilistic data about the objects. We look for  
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After scraping N pages for the same phrase, look for the most highly occurring type words, year numbers, other tags.
After scraping N pages for the same phrase, look for the most highly occurring type words, year numbers, other tags.
== Hints and suggestions ==
While developing, it is easier to use a pre-stored search result/wikipedia page and pre-stored set of pages instead of doing full search and download each time.
However, the system should finally work with any phrases, meaning that the pre-loaded data cannot be normally used.


Additional helpful suggestions and recommendations will be added later during the course.
Additional helpful suggestions and recommendations will be added later during the course.

Redaktsioon: 31. jaanuar 2011, kell 13:59

The main goal of the first lab is to web-scrape data from the public sources using search engines and simple text analysis/statistics.

Conditions

You can do the lab either alone or together with a fellow student. Three students per lab is not ok, though.

Technology - language, op system etc - is completely free.

What should the app do

Your system should take as input a list of arbitrary investigated objects like "Tower Bridge", "Statue of Liberty", "Tallinna raekoda", "Olde hansa", "Tallinn University of Technology", "Andrus Ansip", "Ford focus", "inception" and use web search and web-scraping to obtain probabilistic data about the objects. We look for

  • popularity (search hits)
  • object type (building, church, tower, landmark, person, car, ...)
  • creation year (building year, birthdate, year of introduction to market, ...)
  • other often-used characteristic words/tags (steeple, national, medieval, academic, peaminister, thriller, ...)

The data should be augmented by a numeric confidence measure (0....1) indicating rough trust in the result. The confidence is mostly based on the percentage of investigated pages/sources giving this result, as well as a perceived quality of the data source (like: wikipedia has high quality, arbitrary pages low).

In order to get the list of pages to web scrape you should do several searches, selecting from / using in parallel

  • wikipedia search
  • wolfram alpha search
  • google or bing (or some other) web search

The results should be scraped. Use a different scraping method for semistructured data (wikipedia, wolfram alpha) and unstructured data (arbitrary web pages). For the latter it makes sense to split the page into sentences (just use period . as a separator) and look for sentences containing the investigated phrase. What other words does it contain? What numbers does it contain?

After scraping N pages for the same phrase, look for the most highly occurring type words, year numbers, other tags.

Hints and suggestions

While developing, it is easier to use a pre-stored search result/wikipedia page and pre-stored set of pages instead of doing full search and download each time.

However, the system should finally work with any phrases, meaning that the pre-loaded data cannot be normally used.


Additional helpful suggestions and recommendations will be added later during the course.