Lexical Query Modeling in Session Search

TL;DR

This paper analyzes the effectiveness of lexical query models in session search, revealing that simple term frequency methods perform comparably to specialized models, and discusses their potential and limitations.

Contribution

It provides a comprehensive analysis of lexical query modeling in session search and offers insights into its capabilities and future research directions.

Findings

Naive term frequency methods perform on par with specialized session models.

Lexical query models have notable potential but also limitations in session search.

The paper suggests future research directions for improving session search models.

Abstract

Lexical query modeling has been the leading paradigm for session search. In this paper, we analyze TREC session query logs and compare the performance of different lexical matching approaches for session search. Naive methods based on term frequency weighing perform on par with specialized session models. In addition, we investigate the viability of lexical query models in the setting of session search. We give important insights into the potential and limitations of lexical query modeling for session search and propose future directions for the field of session search.