Stratified Planning
By Yixin Chen, You Xu, Guohui Yao. International Joint Conference on Artificial Intelligence, 2009
326 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/14fbd8613defd10e3a08bb04dfcea02aae0e1c8b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Carlos Castillo
- Alexandros Ntoulas
- Aristides Gionis
- Ravi Kumar
- Fabrizio Silvestri
- Ping Li
- Charu C. Aggarwal
- David Gibson
Citations in the corpus
- Mining Query Logs: Turning Search Usage Data into Knowledge (2010, background): “Many other papers [13, 14, 100, 101] enumerate the major challenges search engine developers must address in order to improve their ability to help users in finding information they need.”
- Introduction to the special topic section on mining Web resources for enhancing information retrieval (2007, background): “It accords with the conclusion of Henzinger [3] that a better page quality estimation algorithm (than PageRank) should involve other sources of information than hyperlink structure analysis.”
- Introducing the Webb Spam Corpus: Using Email Spam to Identify Web Spam Automatically (2006, background): “Web spam is regarded as one of the most important challenges facing search engines and Web users [12] [14], and recent studies suggest that it accounts for a significant portion of all Web content, including 8% of Web pages [11] and 18% of Web sites [13].”
- Comparative study on methods of detecting research fronts using different types of citation (2009, background): “At the same time, it is a challenge for users to evaluate the qualityandauthorityoftheretrievedinformation( Henzinger, Motwani, & Silverstein, 2002; Rieh, 2002).”
- Social Network Analysis and Mining for Business Applications (2011, background): “For instance, search engines cannot function without measures to reduce spam: without such measures, the quality of the rankings suffers severely [Henzinger et al. 2002].”
- Detecting spam web pages through content analysis (2006, background): “[15] acknowledged the impact of web spam on search engine quality.”
- Know your neighbors: web spam detection using the web topology (2007, background): “INTRODUCTION Traditional information retrieval algorithms were developed for relatively small and coherent document collections such as newspaper articles or book catalogs in a library.”
- Discovering Large Dense Subgraphs in Massive Graphs (2005, background): “It is widely acknowledged (see, e.g., [19]) that link spam is one of the most important challenges to web search engines.”