Expert Finding Task
- See: Question Answering Task.
- (Balog et al., 2006) ⇒ Krisztian Balog, Leif Azzopardi, and Maarten de Rijke. (2006). “Formal Models for Expert Finding in Enterprise Corpora.” In: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 2006). doi:10.1145/1148170.1148181
- ABSTRACT: Searching an organization's document repositories for experts provides a cost effective solution for the task of expert finding. We present two general strategies to expert searching given a document collection which are formalized using generative probabilistic models. The first of these directly models an expert's knowledge based on the documents that they are associated with, whilst the second locates documents on topic, and then finds the associated expert. Forming reliable associations is crucial to the performance of expert finding systems. Consequently, in our evaluation we compare the different approaches, exploring a variety of associations along with other operational parameters (such as topicality). Using the TREC Enterprise corpora, we show that the second strategy consistently outperforms the first. A comparison against other unsupervised techniques, reveals that our second model delivers excellent performance.
- (Kautz et al., 1997) ⇒ Henry Kautz, Bart Selman, Mehul Shah. (1997). “The Hidden Web.” In: AI Magazine, 18(2).
- QUOTE: The process of finding an expert who is both reliable and likely to respond to the user can be viewed as a search through the net-work of social relationships between individuals as opposed to a search through the network of hypertext documents. The goal of the REFERRAL WEB Project is to create models of social networks by data mining the web and develop tools that use the models to assist in locating experts and related information search and evaluation tasks.