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Cioaca, Valentin Sergiu; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Numerous approaches have been introduced to automate the process of text summarization, but only few can be easily adapted to multiple languages. This paper introduces a multilingual text processing pipeline integrated in the open-source "ReaderBench" framework, which can be retrofit to cover more than 50 languages. While considering the…
Descriptors: Documentation, Computer Software, Open Source Technology, Algorithms
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Lang, David; Wang, Alex; Dalal, Nathan; Paepcke, Andreas; Stevens, Mitchell L. – AERA Open, 2022
Committing to a major is a fateful step in an undergraduate education, yet the relationship between courses taken early in an academic career and ultimate major issuance remains little studied at scale. Using transcript data capturing the academic careers of 26,892 undergraduates enrolled at a private university between 2000 and 2020, we describe…
Descriptors: Undergraduate Students, Majors (Students), College Planning, Natural Language Processing
Landauer, Thomas K., Ed.; McNamara, Danielle S., Ed.; Dennis, Simon, Ed.; Kintsch, Walter, Ed. – Routledge, Taylor & Francis Group, 2007
"The Handbook of Latent Semantic Analysis" is the authoritative reference for the theory behind Latent Semantic Analysis (LSA), a burgeoning mathematical method used to analyze how words make meaning, with the desired outcome to program machines to understand human commands via natural language rather than strict programming protocols.…
Descriptors: Semantics, Natural Language Processing, Philosophy, Artificial Intelligence
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Chan, Samuel W. K. – Journal of Information Science, 2000
Discusses natural language processing and proposes a novel approach to automatic text segmentation using heterogeneous linguistic knowledge and cluster algorithms. Represents the diversity of textual relations in a discourse network in order to analyze the linguistic bonds and determine the degree of coherence that a text may exhibit. (Author/LRW)
Descriptors: Algorithms, Coherence, Information Retrieval, Linguistic Theory
Peer reviewed Peer reviewed
Tan, Chade-Meng; Wang, Yuan-Fang; Lee, Chan-Do – Information Processing & Management, 2002
Presents an efficient text categorization (or text classification) algorithm for document retrieval of natural language texts that generates bigrams (two-word phrases) and uses the information gain metric, combined with various frequency thresholds. Experimental results suggest that the bigrams can substantially raise the quality of feature sets.…
Descriptors: Algorithms, Classification, Information Retrieval, Natural Language Processing