Query expansion is an important approach utilized to improve the efficiency of data retrieval
tasks. Numerous works are carried out by the researchers to generate fair constructive …

To date, query performance prediction (QPP) in the context of content-based image retrieval
remains a largely unexplored task, especially in the query-by-example scenario, where the …

Understanding the evolution of knowledge has been and will continue to be the key task of
science, technology, and innovation management. Existing research on evolutionary path …

Query performance prediction (QPP) aims to forecast the effectiveness of a search engine
across a range of queries and documents. While state-of-the-art predictors offer a certain …

In order to improve the effectiveness of semantic information retrieval, the improved fish
swarm algorithm is proposed to carry out semantic information retrieval. Firstly, the system of …

Taxonomy alignment is essential for integrating knowledge across diverse domains and
languages, facilitating information retrieval and data integration. Traditional methods heavily …

Marine logistics is one of the main forms of transnational transportation, and the
transportation of goods between multinational companies and even countries must be …

Nowadays, we can use the multi-task learning approach to train a machine-learning
algorithm to learn multiple related tasks instead of training it to solve a single task. In this …

Current entity search models predominantly rely on term frequency and semantic similarity,
often failing to fully exploit the information in the knowledge graphs. This limitation leads to …

Information technology boosts the development of database retrieval in the Chinese digital
humanities domain. However, most database providers adopt a system-oriented design …