Toward improvement of SDR accuracy using LDA and query expansion for SpokenDoc
Kiichi Hasegawa, Sekiya Hideki, Masanori Takehara, Taro Niinomi, Satoshi Tamura, Satoru Hayamizu · 2011
This paper investigates several techniques for spoken document retrieval, toward improvement of retrieval performance based on the conventional method i.e. TF-IDF. The first approach employs rescaled unigrams of LDA to compute a similarity score. The second technique employs query expansion by web retrieval using Yahoo!API. And the third technique is Prioritized And-operator Retrieval based on TF-IDF techniques. We tested these methods using a dry-run data, then it turned out that the third technique is most promising.