Concavity in IR models

Abstract

We study the impact of concavity in IR models and propose to use a generalized logarithm function, the n-logarithm to weight words in documents. We extend the family of information based Information Retrieval (IR) models with this function. We show that that concavity is indeed an important property of IR models. Experiments conducted for IR tasks, Latent Semantic Indexing and Text Categorization show improvements.