Harnessing the wisdom of the crowds for accurate web page clipping

Clipping Web pages, namely extracting the informative clips (areas) from Web pages, has many applications, such as Web printing and e-reading on small handheld devices. Although many existing methods attempt to address this task, most of them can either work only on certain types of Web pages (e.g., news- and bloglike web pages), or perform semi-automatically where extra user efforts are required in adjusting the outputs. The problem of clipping any types of Web pages accurately in a totally automatic way remains pretty much open. To this end in this study we harness the wisdom of the crowds to provide accurate recommendation of informative clips on any given Web pages. Specifically, we leverage the knowledge on how previous users clip similar Web pages, and this knowledge repository can be represented as a transaction database where each transaction contains the clips selected by a user on a certain Web page. Then, we formulate a new pattern mining problem, mining top-1 qualified p...

• Type: Journal
• Year: 2012
• Where: KDD
• Authors: Lei Zhang, Linpeng Tang, Ping Luo, Enhong Chen, Limei Jiao, Min Wang, Guiquan Liu
• Keywords: Accurate Recommendation, Data Mining, Hp Labs, KDD 2012, Knowledge Repository