Learning to rank for Information Retrieval (IR) is a task to automatically construct a ranking
model using training data, such that the model can sort new objects according to their …

In machine learning, hyperparameter tuning is the problem of choosing a set of optimal
hyperparameters for a learning algorithm. Several approaches have been widely adopted …

The prediction of query performance is an interesting and important issue in Information
Retrieval (IR). Current predictors involve the use of relevance scores, which are time …

Words in a document that are frequently occurring but meaningless in terms of Information
Retrieval (IR) are called stopwords. It is repeatedly claimed that stopwords do not contribute …

US7702611B2 - Method for automatically performing conceptual highlighting in electronic text
- Google Patents US7702611B2 - Method for automatically performing conceptual highlighting …

We introduce the hypergeometric models KL, DLH and DLLH using the DFR approach, and
we compare these models to other relevant models of IR. The hypergeometric models are …

Nowadays, searching the relevant documents from a large dataset becomes a big
challenge. Automatic query expansion is one of the techniques, which addresses this …

The term frequency normalisation parameter tuning is a crucial issue in information retrieval
(IR), which has an important impact on the retrieval performance. The classical pivoted …

Content generated on intra-organizational blogging platforms may help managers
understand the emerging ideas, issues, and opportunities of their companies, whereas the …

Abstract Information Retrieval system retrieves relevant documents from large datasets.
Automatic Query Expansion (AQE) is one of the approaches to enhance IR performance by …