Jianchang Mao
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ACM Queue | 2004
Rajat Mukherjee; Jianchang Mao
The last decade has witnessed the growth of information retrieval from a boutique discipline in information and library science to an everyday experience for billions of people around the world. This revolution has been driven in large measure by the Internet, with vendors focused on search and navigation of Web resources and Web content management. Simultaneously, enterprises have invested in networking all of their information together to the point where it is increasingly possible for employees to have a single window into the enterprise. Although these employees seek Web-like experiences in the enterprise, the Internet and enterprise domains differ fundamentally in the nature of the content, user behavior, and economic motivations.
conference on information and knowledge management | 2002
Christina Chung; Raymond Lieu; Jinhui Liu; Alpha Luk; Jianchang Mao; Prabhakar Raghavan
Verity Inc. has developed a comprehensive suite of tools for accurately and efficiently organizing enterprise content which involves four basic steps: (i) creating taxonomies, (ii) building classification models, (iii) populating taxonomies with documents, and (iv) deploying populated taxonomies in enterprise portals. A taxonomy is a hierarchical representation of categories. A taxonomy provides a navigation structure for exploring and understanding the underlying corpus without sifting through a huge volume of documents. Thematic Mapping automatically discovers a concept tree from a corpus of unstructured documents and assigns meaningful labels to concepts based on a semantic network. Integrating with Verity Intelligent Classifiers user-friendly GUI, a user can drill down a concept tree for navigation, perform a conceptual search to retrieve documents pertaining to a concept, build a taxonomy from the concept tree, as well as edit a taxonomy to tailor it into various views (customized taxonomies) of the same corpus. Classification rules can be generated automatically from concepts. These classification rules can be used for populating documents into the taxonomy.
web intelligence | 2005
Mani Abrol; Bhavin Doshi; Jim Kanihan; Amit Kumar; Jinhui Liu; Jianchang Mao
The taxonomy is the most popular way for organizing a large volume of content. A taxonomy, which is typically a hierarchical representation of categories, provides a navigation structure for exploring and understanding the underlying corpus without sifting through a huge volume of documents. Creating and maintaining taxonomies with a large volume of documents remains a daunting task facing many enterprises. Content organization process typically involves four basic steps: (i) creating taxonomies; (ii) building classification models; (iii) populating taxonomies with documents; and (iv) deploying populated taxonomies in enterprise portals. Each step in the process may have unique requirements that determine what techniques and tools are suitable for the tasks. In this paper, we present a comprehensive suite of tools developed by Verity Inc. for accurately, collaboratively, and efficiently organizing enterprise content.
Archive | 2002
Christina Chung; Jinhui Liu; Alpha Luk; Jianchang Mao; Sumit Taank; Vamsi Vutukuru
Archive | 2001
Jianchang Mao; Mani Abrol; Rajat Mukherjee; Michel Tourn; Prabhakar Raghavan
Archive | 2003
Jianchang Mao; Sumit Taank; Christina Chung; Alpha Luk
Archive | 2001
Ashok K. Chandra; Neil Latarche; Jianchang Mao; Prabhakar Raghavan
Archive | 2001
Jianchang Mao; Rajat Mukherjee; Prabhakar Raghavan; Panayiotis Tsaparas
very large data bases | 2001
Mani Abrol; Neil Latarche; Uma Mahadevan; Jianchang Mao; Rajat Mukherjee; Prabhakar Raghavan; Michel Tourn; John Wang; Grace Zhang
Archive | 2006
Jianchang Mao; Zhichen Xu; Chad Walters; John Wang; Albert Meltzer