Query expansion is a long-studied approach for improving retrieval effectiveness by enhancing the user's original query with additional related words. Current algorithms for ...
We present a novel approach that transforms the weighting task to a typical coarse-grained classification problem, aiming to assign appropriate weights for candidate expansion term...
User generated content is characterized by short, noisy documents, with many spelling errors and unexpected language usage. To bridge the vocabulary gap between the user's in...
Wouter Weerkamp, Krisztian Balog, Maarten de Rijke
The vocabulary of the TREC Legal OCR collection is noisy and huge. Standard techniques for improving retrieval performance such as content-based query expansion are ineffective fo...
We propose a novel probabilistic method based on the Hidden Markov Model (HMM) to learn the structure of a Latent Variable Model (LVM) for query language modeling. In the proposed...