Automatic resource compilation by analyzing hyperlink structure and associated text
read more
Citations
A query paradigm to discover the relation between text and images
Incremental web search: tracking changes in the web
Harnessing the hyperlink structure of the Web
Automatic web resource compilation using data mining
Selective Approach To Handling Topic Oriented Tasks On The World Wide Web
References
The anatomy of a large-scale hypertextual Web search engine
The Anatomy of a Large-Scale Hypertextual Web Search Engine.
Authoritative sources in a hyperlinked environment
Silk from a sow's ear: extracting usable structures from the Web
Related Papers (5)
Frequently Asked Questions (7)
Q2. How do the authors normalize the entries of h and a?
Since many entries of W are larger than one, the entries of h and a may grow as the authors iterate; however, since the authors only need their relative values, the authors normalize after each iteration to keep the entries small.
Q3. How long does it take to compute a resource list?
The iterative computation at the core of the analysis takes about a second for a single resource list, on a variety of modern platforms.
Q4. What are the usual concerns that Web users express while searching for resources?
Web users express while searching for resources, which are related to the notions of recall and precision in the Information Retrieval literature.
Q5. What is the emphasis of the experiment?
The emphasis in their current implementation has not been heavy-duty performance (in that the authors do not envision their system fielding thousands of queries per second and producing answers in real time); instead, the authors focused on the quality of their resource lists.
Q6. What is the important reason why the authors decided to fix k to 5.2.1?
In their case, a very small value of k is sufficient -- and hence the computation can be performed extremely efficiently -- for two reasons.
Q7. What is the purpose of the algorithm?
Their work is oriented in a different direction - namely, to use links as a means of harnessing the latent human annotation in hyper-links so as to broaden a user search and focus on a type of ‘high-quality’ page.