Joshua Lutes

• Brigham Young University

Named entity recognition applied to scanned and OCRed historical documents can contribute to the discoverability of historical information. However, entity recognition from some historical corpora is much more difficult than from natively digital text because of the marked presence of word errors and absence of page layout information. How difficul...

Named entity recognition from scanned and OCRed historical documents can contribute to historical research. However, entity recogni-tion from historical documents is more diffi-cult than from natively digital data because of the presence of word errors and the absence of complete formatting information. We ap-ply four extraction algorithms to vario...

Topic models have been shown to reveal the semantic content in large corpora. Many individualized visualizations of topic models have been reported in the lit-erature, showing the potential of topic models to give valuable insight into a cor-pus. However, good, general tools for browsing the entire output of a topic model along with the analyzed co...