A Comparison of Two Unsupervised Table Recognition Methods from Digital Scientific Articles

An Unsupervised Machine Learning Approach to Body Text and Table of Contents Extraction from Digital Scientific Articles

Scientific articles are predominantly stored in digital document formats, which are optimised for presentation, but lack structural information. This poses challenges to access the documents’ content, for example for information retrieval. We have developed a processing pipeline that makes use of unsupervised machine learning techniques and heuristics to detect the logical structure of a PDF do...

Unsupervised and domain-independent extraction of technical terms from scientific articles in digital libraries

A central issue for making the contents of documents in a digital library accessible to the user is the identification and extraction of technical terms. We propose a method to solve this task in an unsupervised, domain-independent way: We use a nominal group chunker to extract term candidates and select the technical terms from these candidates based on string frequencies retrieved using the M...

Deficit irrigation for corn: a comparison of two methods

on the comparison of keyword and semantic-context methods of learning new vocabulary meaning

the rationale behind the present study is that particular learning strategies produce more effective results when applied together. the present study tried to investigate the efficiency of the semantic-context strategy alone with a technique called, keyword method. to clarify the point, the current study seeked to find answer to the following question: are the keyword and semantic-context metho...

comparison of the amount of debris extruded apically in two rotary techniques: flexmaster and m2

چکیده ندارد.