HTrec

HTrec, short for *Heterogeneous Text Retrieval Conference*, is an annual workshop series focused on evaluating and advancing information retrieval (IR) systems for heterogeneous text collections. Organized as part of the Text REtrieval Conference (TREC) series, HTrec aims to address challenges in retrieving relevant information from diverse and complex document sets, such as those containing mixed media, multilingual content, or structured and unstructured data.

The workshop emerged from the need to improve retrieval performance across varied text formats, including web pages, social media posts, scientific literature, and other unstructured or semi-structured sources. HTrec evaluates systems using benchmark datasets and predefined tasks, such as cross-lingual retrieval, multilingual document clustering, or retrieval from mixed-language corpora. Participants submit their retrieval models, which are then assessed based on standard metrics like precision, recall, and mean average precision (MAP).

HTrec has contributed significantly to research in multilingual and heterogeneous information retrieval by fostering collaboration among academics, industry practitioners, and researchers. It provides a platform for discussing novel approaches, such as deep learning-based retrieval, cross-language information access, and the integration of metadata for improved relevance ranking. The workshop also highlights real-world applications, including search engines, digital libraries, and knowledge discovery systems.

Since its inception, HTrec has evolved alongside advancements in IR technology, incorporating emerging challenges like retrieval from social media, multilingual question answering, and the integration of multimedia content. The workshop remains a key event for researchers seeking to refine retrieval techniques for diverse and dynamic text environments.