C4.5: programs for machine learning
C4.5: programs for machine learning
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Does “authority” mean quality? predicting expert quality ratings of Web documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Empirically validated web page design metrics
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Effective site finding using link anchor information
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Web page change and persistence---a four-year longitudinal study
Journal of the American Society for Information Science and Technology
Usability Engineering
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Developing and validating an instrument for measuring user-perceived web quality
Information and Management
Assessing a Firm's Web Presence: A Heuristic Evaluation Procedure for the Measurement of Usability
Information Systems Research
Web Site Usability, Design, and Performance Metrics
Information Systems Research
Challenges in web search engines
ACM SIGIR Forum
Query-independent evidence in home page finding
ACM Transactions on Information Systems (TOIS)
Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search
IEEE Transactions on Knowledge and Data Engineering
Efficient pagerank approximation via graph aggregation
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Search Engine Marketing, Inc.: Driving Search Traffic to Your Company's Web Site
Search Engine Marketing, Inc.: Driving Search Traffic to Your Company's Web Site
The influence of search engines on preferential attachment
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Learning to crawl: Comparing classification schemes
ACM Transactions on Information Systems (TOIS)
Topical TrustRank: using topicality to combat web spam
Proceedings of the 15th international conference on World Wide Web
Beyond PageRank: machine learning for static ranking
Proceedings of the 15th international conference on World Wide Web
Prioritizing Web Usability
Understanding web home page perception
European Journal of Information Systems
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Improving Linkage of Web Pages
INFORMS Journal on Computing
Clustering-based incremental web crawling
ACM Transactions on Information Systems (TOIS)
Two New Prediction-Driven Approaches to Discrete Choice Prediction
ACM Transactions on Management Information Systems (TMIS)
Sentimental Spidering: Leveraging Opinion Information in Focused Crawlers
ACM Transactions on Information Systems (TOIS)
Goal attainment on long tail web sites: An information foraging approach
Decision Support Systems
| Hi-index | 0.00 |
The World Wide Web has become a key intermediary between producers and consumers of information. Web's linkage structure has been exploited by contemporary search engines to decrease the search cost for consumers while usually also rewarding the producers of higher status Web pages. In addition to influencing visibility and accessibility, in-links, as marks of recognition, accord status to a Web page. In this paper we show how Web page status may be predicted at least in part by page location and topic specificity. Moreover, we observe that the “philanthropic” contributions of a Web page---specifically, contributions of information brokerage function---are also good predictors of in-links. The observations are made in the presence of domain-and topic-specific effects. Interestingly, all of these features that may predict status are “local” to a given Web page and within the control of the owner/author of the page. This is in contrast to the “global” nature of Web linkage-based metrics such as in-link count that are derived as a result of downloading and indexing billions of pages. Because the linkage structure of the Web affects browsing, crawling, and retrieval, our results have implications for vertical and general search, business intelligence, and content management.