@inproceedings{7a346759c79d4f2caf823f6ab4039b39,
title = "Informing the curious negotiator: Automatic news extraction from the internet",
abstract = "Information acquisition and validation play an important role in the decision making process during negotiation. In this chapter we briefly present the framework of a smart data mining system for providing contextual information extracted from the Internet to a negotiation agent. We then present one of its components in more details - an effective automated technique for extracting relevant articles from news web sites, so that they can be used further by the mining agents. Most current techniques experience difficulties in coping with changes in web site structure and formats. The proposed extraction process is completely automatic and independent of web site formats. Proposed technique identifies regularities in both format and content of news web sites. The algorithms are applicable to both single- and multi-document web sites. Since invalid URLs can cause errors in data extraction, we also present a method for the negotiation agent to estimate the validity of the extracted data based on the frequency of the relevant words in the news title. Once the news articles are extracted the next task is to construct sets of given articles. This chapter presents a new procedure for constructing news data sets on given topics. The extracted news data set is further utilised by the parties involved in negotiation. The information retrieved from the data set can support both human and automated negotiators.",
author = "Debbie Zhang and Simoff, {Simeon J.}",
year = "2006",
doi = "10.1007/11677437_14",
language = "English",
isbn = "3540325476",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "176--191",
booktitle = "Data Mining",
}