Error Detection, Recovery, and Repair in the Translation of Inorganic Nomenclatures. 3. An Error Handler

Self Cite

The treatment of errors generated in the transmission of chemical information from humans to machines is examined. Every type of human-machine communication requires a translation subprocess to deal with the various possible representations of knowledge; the present study was designed to consider errors occurring in such a subsystem. Regardless of the model employed, translation of knowledge is performed over several successive stages; at each stage different types of errors may be detected. A method is proposed to classify these errors according to the stage at which they occur, thus facilitating the generalization of the process. An analysis of errors occurring during the translation of inorganic chemical names is also presented. The particular grammatical features of different nomenclatures would require a study of the errors appearing in the human-machine communication process in modern chemistry-oriented systems, a problem which has only been touched upon in the systems proposed to date. Attention here is centered on lexicographic errors, since that stage of the translation process is completely independent of the model employed and might thus be useful in a more general sense.

Section: Discussionmentioning

confidence: 99%

“…Such a system would be based on a model that could be applied to chemical names. One possible system is presented elsewhere. , …”

Section: Discussionmentioning

confidence: 99%

Error Detection, Recovery, and Repair in the Translation of Inorganic Nomenclatures. 1. A Study of the Problem

Ruiz

Soto

Gómez‐Nieto

1996

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“…The definition of the syntax of the grammar defining the language. This is a simple definition based on morpheme category or type and defines how these may be introduced into a string representing an inorganic chemical name, as will be described for inorganic nomenclatures in the next article in this series …”

Section: Discussionmentioning

confidence: 99%

“…The next article in this series describes the application of the proposed model to the repair of lexical errors that may arise in the recognition of inorganic chemical names in the most commonly-used nomenclatures (IUPAC, Stock, and Conventional) …”

Section: Discussionmentioning

confidence: 99%

Error Detection, Recovery, and Repair in the Translation of Inorganic Nomenclatures. 2. A Proposed Strategy

Ruiz

Soto

Gómez‐Nieto

1996

Self Cite

The repair of lexicographic errors occuring during the computer translation of knowledge is performed by approximate string matching algorithms. This article presents a new algorithm that attempts to repair lexical errors in inorganic chemical names. The algorithm allows the repair of an incorrect string containing one or more errors due to deletion, insertion, or transposition of multiple characters. Repair may be carried out on all or only part of the incorrect string, so the algorithm may be used to repair strings containing more than one incorrect morpheme. A model is proposed for the use of this algorithm in the repair of lexical errors in inorganic chemical names. The model attempts to generate a set of possible repair strings free from either syntactic or lexicographic errors. Repair is performed by comparing all or part of the error string with the set of terminal symbols or morphemes included in the grammar. A new model is proposed for the calculation of similarity; it is highly discriminating and allows the repair of parts of an error string.

How To Add Chemical Abstracts Service Registry Numbers and Structures to Databases via Chemical Names Comparison

Krebs

Jordis

2000