Xu: An Automated Query Expansion and Optimization Tool
Morgan Gallant, Haruna Isah, Farhana Zulkernine, Shahzad Khan

TL;DR
Xu is an automated query expansion tool that uses high-dimensional clustering and an open API to improve information retrieval by expanding user queries with semantically similar words, achieving high accuracy.
Contribution
The paper introduces Xu, a scalable and robust automated query expansion method combining clustering and API-based semantic similarity, which outperforms existing tools.
Findings
Xu achieved 88% accuracy compared to human-generated queries.
Xu outperformed Datamuse in semantic query expansion.
The tool is effective on news article datasets.
Abstract
The exponential growth of information on the Internet is a big challenge for information retrieval systems towards generating relevant results. Novel approaches are required to reformat or expand user queries to generate a satisfactory response and increase recall and precision. Query expansion (QE) is a technique to broaden users' queries by introducing additional tokens or phrases based on some semantic similarity metrics. The tradeoff is the added computational complexity to find semantically similar words and a possible increase in noise in information retrieval. Despite several research efforts on this topic, QE has not yet been explored enough and more work is needed on similarity matching and composition of query terms with an objective to retrieve a small set of most appropriate responses. QE should be scalable, fast, and robust in handling complex queries with a good response…
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