TY - GEN
T1 - The cluster hypothesis in information retrieval
AU - Kurland, Oren
PY - 2014
Y1 - 2014
N2 - The cluster hypothesis states that "closely associated documents tend to be relevant to the same requests" [45]. This is one of the most fundamental and influential hypotheses in the field of information retrieval and has given rise to a huge body of work. In this tutorial we will present the research topics that have emerged based on the cluster hypothesis. Specific focus will be placed on cluster-based document retrieval, the use of topic models for ad hoc IR, and the use of graph-based methods that utilize inter-document similarities. Furthermore, we will provide an in-depth survey of the suite of retrieval methods that rely, either explicitly or implicitly, on the cluster hypothesis and which are used for a variety of different tasks; e.g., query expansion, query-performance prediction, fusion and federated search, and search results diversification.
AB - The cluster hypothesis states that "closely associated documents tend to be relevant to the same requests" [45]. This is one of the most fundamental and influential hypotheses in the field of information retrieval and has given rise to a huge body of work. In this tutorial we will present the research topics that have emerged based on the cluster hypothesis. Specific focus will be placed on cluster-based document retrieval, the use of topic models for ad hoc IR, and the use of graph-based methods that utilize inter-document similarities. Furthermore, we will provide an in-depth survey of the suite of retrieval methods that rely, either explicitly or implicitly, on the cluster hypothesis and which are used for a variety of different tasks; e.g., query expansion, query-performance prediction, fusion and federated search, and search results diversification.
UR - http://www.scopus.com/inward/record.url?scp=84899939910&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-319-06028-6_105
DO - https://doi.org/10.1007/978-3-319-06028-6_105
M3 - منشور من مؤتمر
SN - 9783319060279
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 823
EP - 826
BT - Advances in Information Retrieval - 36th European Conference on IR Research, ECIR 2014, Proceedings
T2 - 36th European Conference on Information Retrieval, ECIR 2014
Y2 - 13 April 2014 through 16 April 2014
ER -