Automatic query reformulation is a widely utilized technology for enriching user
requirements and enhancing the outcomes of code search. It can be conceptualized as a …

Sažetak Query, expressing the user need and requirement, has an important role, in an
information retrieval system, for reaching a high accuracy search. In this paper, we present …

Legal case retrieval, which aims to retrieve relevant cases to a given query case, benefits
judgment justice and attracts increasing attention. Unlike generic retrieval queries, legal …

Dense retrieval is widely used for entity linking to retrieve entities from large-scale
knowledge bases. Mainstream techniques are based on a dual-encoder framework, which …

Models for conversational question answering (ConvQA) over knowledge graphs (KGs) are
usually trained and tested on benchmarks of gold QA pairs. This implies that training is …

In the growing information retrieval (IR) world, selecting suitable keywords and generating
queries is important for effective retrieval. Modern database applications need a …

Pre-trained language models have achieved great success in various large-scale
information retrieval tasks. However, most of pretraining tasks are based on counterfeit …

Recent empirical studies have shown that while neural rankers exhibit increasingly higher
retrieval effectiveness on tasks such as ad hoc retrieval, these improved performances are …

In modern search engines, synonyms are widely used for query reformulation to improve
search recall and relevance. The search query is reformulated based on the synonymous …

Hyper-relational knowledge graph contains the main triple and additional information
(qualifiers). The additional information can assist the main triple to predict missing entities …