On derived data services in cyberspace

We propose a framework, called derived data services (DDS), to ease the tension between (a) the need to mine individual's Web usage logs across multiple sites for aiding in personalization, and (b) the inherent privacy risks in it. In DDS, a standardized, hierarchical, format can be developed, whereby some higher level abstractions from a usage log can be captured, and potentially used across multiple applications. The hierarchical data structure also allows derived data to be processed incrementally based on the level of information needed, and on the level of privacy an individual wishes to have. The derived data summarizes an individual's profile in cyberspace, and should be the legal property of the individual so that access to the profile must be legally authorized by the person.

[1]  W. Litwin,et al.  An overview of the multi-database manipulation language MDSL , 1987, Proceedings of the IEEE.

[2]  Kristian J. Hammond,et al.  Mining navigation history for recommendation , 2000, IUI '00.

[3]  Lorrie Faith Cranor,et al.  The platform for privacy preferences , 1999, CACM.

[4]  Ibrahim Cingil,et al.  A broader approach to personalization , 2000, CACM.

[5]  Gediminas Adomavicius,et al.  Using Data Mining Methods to Build Customer Profiles , 2001, Computer.

[6]  Marc Langheinrich,et al.  The platform for privacy preferences 1.0 (p3p1.0) specification , 2002 .

[7]  Thorsten Joachims,et al.  Web Watcher: A Tour Guide for the World Wide Web , 1997, IJCAI.

[8]  Katia P. Sycara,et al.  WebMate: a personal agent for browsing and searching , 1998, AGENTS '98.

[9]  Scott Boag,et al.  XQuery 1.0 : An XML Query Language , 2007 .

[10]  Dan Brickley,et al.  Rdf vocabulary description language 1.0 : Rdf schema , 2004 .

[11]  Dan Brickley,et al.  Resource Description Framework (RDF) Model and Syntax Specification , 2002 .

[12]  James Clark,et al.  XSL Transformations (XSLT) Version 1.0 , 1999 .

[13]  Markus Jakobsson,et al.  Privacy-preserving global customization , 2000, EC '00.

[14]  S. Weibel,et al.  RFC 2413: Dublin core metadata for resource discovery , 1998 .

[15]  Ibrahim Cingil,et al.  Supporting global user profiles through trusted authorities , 2002, SGMD.

[16]  Rynson W. H. Lau,et al.  Multi-resolution cache management in digital virtual library , 1998, Proceedings IEEE International Forum on Research and Technology Advances in Digital Libraries -ADL'98-.

[17]  Vibhu O. Mittal,et al.  OCELOT: a system for summarizing Web pages , 2000, SIGIR '00.

[18]  Gerard Salton,et al.  Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer , 1989 .

[19]  Adele E. Howe,et al.  Incremental clustering for profile maintenance in information gathering web agents , 2001, AGENTS '01.

[20]  Hongyuan Zha,et al.  Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering , 2002, SIGIR '02.

[21]  Timothy W. Finin,et al.  Yahoo! as an ontology: using Yahoo! categories to describe documents , 1999, CIKM '99.

[22]  Oren Etzioni,et al.  Adaptive Web sites , 2000, CACM.

[23]  James A. Hendler,et al.  Owl web ontology language 1 , 2002 .

[24]  Building universal profile systems over a peer-to-peer network , 2003, Proceedings the Third IEEE Workshop on Internet Applications. WIAPP 2003.

[25]  Zhiqiang Zheng,et al.  Personalization from incomplete data: what you don't know can hurt , 2001, KDD '01.

[26]  Alin Deutsch,et al.  XML-QL: A Query Language for XML , 1998 .

[27]  Thomas C. Kinnear,et al.  Marketing Research: An Applied Approach , 2000 .

[28]  David C. Fallside,et al.  Xml schema part 0: primer , 2000 .