Machine learning techniques to mine the Web and other
information networks, social networks, and social media.
Crawling, indexing, ranking and filtering algorithms using content
and link analysis. Applications to search, classification,
recommendation, and Web intelligence.
Group project on one of the topics covered in class.
This course is open to CS, Informatics, SLIS, CogSci, and other
graduate students with an interest in information systems,
artificial intelligence, and Web science. Although prior
exposure to machine learning algorithms, information
retrieval, and/or Web programming is helpful, there are
no advanced AI or DB prerequisites. Strong coding skills
(in any language) are highly recommended.
|| Web Data Mining:
Exploring Hyperlinks, Contents, and Usage Data by
(with a chapter on crawling by yours truly,
here), Springer, 2007. The second edition came out in 2011; either edition is fine for this course.
Another excellent reference is Mining
the Web by Soumen Chakrabarti, Morgan-Kaufmann,
2002, which we used in past offerings of this course. Note the second edition of this book is in the making.
|| TR 2:30-3:45P in I (Informatics West) 107 (map)
|| Fil Menczer (Office hours by appointment in Info East 314; please schedule in class)
|| Mohsen (Office hours Tu-Th 10am-noon)
||Please use the group discussions for all class-related questions and
communications, unless privacy is necessary.