Data Brokers: Building Collections through Automated Negotiation

  • Fillia Makedon
  • Song Ye
  • Sheng Zhang
  • James Ford
  • Li Shen
  • Sarantos Kapidakis
Conference paper

DOI: 10.1007/978-3-540-24674-9_3

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3025)
Cite this paper as:
Makedon F., Ye S., Zhang S., Ford J., Shen L., Kapidakis S. (2004) Data Brokers: Building Collections through Automated Negotiation. In: Vouros G.A., Panayiotopoulos T. (eds) Methods and Applications of Artificial Intelligence. SETN 2004. Lecture Notes in Computer Science, vol 3025. Springer, Berlin, Heidelberg

Abstract

Collecting digital materials is time-consuming and can gain from automation. Since each source – and even each acquisition – may involve a separate negotiation of terms, a collector may prefer to use a broker to represent his interests with owners. This paper describes the Data Broker Framework (DBF), which is designed to automate the process of digital object acquisition. For each acquisition, a negotiation agent is assigned to negotiate on the collector’s behalf, choosing from strategies in a strategy pool to automatically handle most bargaining cases and decide what to accept and what counteroffers to propose. We introduce NOODLE (Negotiation OntOlogy Description LanguagE) to formally specify terms in the negotiation domain.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Fillia Makedon
    • 1
  • Song Ye
    • 1
  • Sheng Zhang
    • 1
  • James Ford
    • 1
  • Li Shen
    • 1
  • Sarantos Kapidakis
    • 2
  1. 1.Department of Computer ScienceThe Dartmouth Experimental Visualization Laboratory (DEVLAB) 
  2. 2.Department of Archive and Library SciencesIonian UniversityGreece

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