68 research outputs found
音声翻訳における文解析技法について
本文データは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルを基にpdf変換したものである京都大学0048新制・論文博士博士(工学)乙第8652号論工博第2893号新制||工||968(附属図書館)UT51-94-R411(主査)教授 長尾 真, 教授 堂下 修司, 教授 池田 克夫学位規則第4条第2項該当Doctor of EngineeringKyoto UniversityDFA
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Extraction of chemical structures and reactions from the literature
The ever increasing quantity of chemical literature necessitates
the creation of automated techniques for extracting relevant information.
This work focuses on two aspects: the conversion of chemical names to
computer readable structure representations and the extraction of chemical
reactions from text.
Chemical names are a common way of communicating chemical structure
information. OPSIN (Open Parser for Systematic IUPAC Nomenclature), an
open source, freely available algorithm for converting chemical names to
structures was developed. OPSIN employs a regular grammar to direct
tokenisation and parsing leading to the generation of an XML parse tree.
Nomenclature operations are applied successively to the tree with many
requiring the manipulation of an in-memory connection table representation
of the structure under construction. Areas of nomenclature supported are
described with attention being drawn to difficulties that may be
encountered in name to structure conversion. Results on sets of generated
names and names extracted from patents are presented. On generated names,
recall of between 96.2% and 99.0% was achieved with a lower bound of 97.9%
on precision with all results either being comparable or superior to the
tested commercial solutions. On the patent names OPSIN s recall was 2-10%
higher than the tested solutions when the patent names were processed as
found in the patents. The uses of OPSIN as a web service and as a tool for
identifying chemical names in text are shown to demonstrate the direct
utility of this algorithm.
A software system for extracting chemical reactions from the text of
chemical patents was developed. The system relies on the output of
ChemicalTagger, a tool for tagging words and identifying phrases of
importance in experimental chemistry text. Improvements to this tool
required to facilitate this task are documented. The structure of chemical
entities are where possible determined using OPSIN in conjunction with a
dictionary of name to structure relationships. Extracted reactions are
atom mapped to confirm that they are chemically consistent. 424,621 atom
mapped reactions were extracted from 65,034 organic chemistry USPTO
patents. On a sample of 100 of these extracted reactions chemical entities
were identified with 96.4% recall and 88.9% precision. Quantities could be
associated with reagents in 98.8% of cases and 64.9% of cases for products
whilst the correct role was assigned to chemical entities in 91.8% of
cases. Qualitatively the system captured the essence of the reaction in
95% of cases. This system is expected to be useful in the creation of
searchable databases of reactions from chemical patents and in
facilitating analysis of the properties of large populations of reactions
Meaning versus Grammar
This volume investigates the complicated relationship between grammar, computation, and meaning in natural languages. It details conditions under which meaning-driven processing of natural language is feasible, discusses an operational and accessible implementation of the grammatical cycle for Dutch, and offers analyses of a number of further conjectures about constituency and entailment in natural language
Techniques for searching, parsing, and matching (fourth edition)
These lecture notes present some basic techniques for: (i) exploring search spaces, (ii) parsing context-free languages, and (iii) matching patterns in strings. These techniques are taught in a course on Automata, Languages, and Translators at the University of Roma "Tor Vergata''. We assume that the reader is familiar with the basic notions of Automata Theory and Formal Languages. These notions can be found in many books such as [Har78,HoU79,Pet13a].
Some of the algorithms we have presented in these notes are written in Java 1.5 and some others in Prolog. For the Java language the reader may refer to the Java Tutorial at http://java.sun.com/docs/books/tutorial/} .
(Recall that this Java version allows the use of parameterized types, also called generics.) All Java programs have been compiled using the Java compiler 1.5.0-13 running under Mac OS X 10.4.11 Darwin 8.11.1.
For the Prolog language the reader may refer to [ClM84]. The Prolog language incorporates a backtracking mechanism which is useful for exploring search spaces and solving parsing and matching problems
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