In-Su Kang

TL;DR: Experimental result extensively shows that the passage retrieved using the completely-arbitrary passage significantly improves the document retrieval, as well as the passage retrieval using previous non-completely arbitrary passages, on six standard TREC test collections, in the context of language modeling approaches.

TL;DR: This work tries to generate a summary in source language, using translated documents by a machine translator and a summarization system in target language, and shows the possibility of multi-documents summarization, using crosslanguage texts.

TL;DR: This paper proposes a new type of passage, called completely-arbitrary passage, which consists of passage-retrieval and passage-extension as sub-steps, unlike previous single-stage passage feedback relying only on passage retrieval.

TL;DR: This paper uses a combination strategy that integrates words and n-grams at the ranked list level and attempts a dictionary-based bi-directional combination of query translation and document translation for cross-language information retrieval.