New Book on Web Mining

Web Data Mining - Exploring Hyperlinks, Contents and Usage Data, written by Bing Liu, is going to be published at the end of year 2006.

Jon Kleinberg got one more prestigious award

The Nevanlinna Prize at the ICM2006 has been awarded to Jon Kleinberg. His work is on the mathematics of Information Networks.

The Porter Stemming Algorithm

The 'official’ page for distribution of the Porter Stemming Algorithm has been revised and moved.

For Python (and other script languages), it is probably more efficient to use a C-implemented module (e.g., nltk.stemmer.porter) rather than taking the Python code straightforwardly.

Minorthird

MinorThird is a collection of Java classes for storing text, annotating text, and learning to extract entities and categorize text. It was written primarily by Dr William W. Cohen. It comes with a collection of publically-available extraction problems in Minorthird format (about 2Mb).

Minorthird differs from existing NLP and learning toolkits in a number of ways:

• Unlike many NLP packages (eg GATE, Alembic) it combines tools for annotating and visualizing text with state-of-the art learning methods.


• Unlike many other learning packages, it contains methods to visualize both training data and the performance of classifiers, which facilitates debugging.


• Unlike other learning packages less tightly integrated with text manipulation tools, it is possible to track and visualize the transformation of text data into machine learning data.


• Unlike many packages (including WEKA), it is open-source, and available for both commercial and research purposes.


• Unlike any open-source learning systems I know of, it is architected to support active learning and on-line learning, which should facilitate integration of learning methods into agents.

Information Retrieval Textbooks

• C. J. "Keith" van Rijsbergen, Information Retrieval. Classic. Free online.
• Bill Frakes and Ricardo Baeza-Yates, Information Retrieval Data Structures & Algorithms. Technical. With source code.
• Ricardo Baeza-Yates and Berthier Ribeiro-Neto, Modern Information Retrieval. Popular.
• Ian H. Witten, Alistair Moffat and Timothy C. Bell, Managing Gigabytes: Compressing and Indexing Documents and Images. Tight integration with data compression. Its companion software MG is open source and wide-spreaded.
• William Hersh, Information Retrieval: A Health and Biomedical Perspective. Primer. Domain specific.
• Peter Jackson and Isabelle Moulinier, Natural Language Processing for Online Applications: Text Retrieval, Extraction & Categorization. Biased to text mining.
• David A. Grossman, Ophir Frieder. Information Retrieval : Algorithms and Heuristic in the Springer The Information Retrieval Series. A very clear "fundamentals" book for students and practitioners.
• Richard K. Belew, Find Out About: Search Engine Technology from a Cognitive Perspective.
• Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze. Introduction to Information Retrieval. On the way. Desirable
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