Contributions to Books:

S. Bashir, A. Rauber:
"Retrieval Models Versus Retrievability";
in: "Current Challenges in Patent Information Retrieval", issued by: Springer; Springer, Belrin, 2017, ISBN: 978-3-662-53817-3, 185 - 212.

English abstract:
Retrievability is an important measure in information retrieval that can
be used to analyze retrieval models and document collections. Rather than
just focusing on a set of few documents that are given in the form of rel-
evance judgments, retrievability examines what is retrieved, how frequently
it is retrieved, and how much effort is needed to retrieve it. Such a mea-
sure is of particular interest within the recall oriented retrieval systems (e.g.
patent or legal retrieval), because in this context a document needs to be
retrieved before it can be judged for relevance. If a retrieval model makes
some patents hard to find, patent searchers could miss relevant documents
just because of the bias of the retrieval model. In this chapter we explain the
concept of retrievability in information retrieval. We also explain how it can
be estimated and how it can be used for analysing a retrieval bias of retrieval
models. We also show how retrievability relates to effectiveness by analysing
the relationship between retrievability and effectiveness measures and how
the retrievability measure can be used to improve effectiveness.

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.