Developing an innovative entity extraction method for unstructured data

<span id="docs-internal-guid-5dcc170c-7fff-e8e4-10d4-4a07701ca923"><span>Unstructured data becomes challenges because in recent years have observed the ability to gather a massive amount of data from annotated documents. This paper interested with Arabic unstructured text analysis. Manipulating unstructured text and converting it into a form understandable by computer is a high-level aim. An important step to achieve this aim is to understand numerical phrases. This paper aims to extract numerical data from Arabic unstructured text in general. This work attempts to recognize numerical characters phrases, analyze them and then convert them into integer values. The inference engine is based on the Arabic linguistic and morphological rules. The applied method encompasses rules of numerical nouns with Arabic morphological rules, in order to achieve high accurate extraction method. Arithmetic operations are applied to convert the numerical phrase into integer value. The proper operation is determined depending on linguistic and morphological rules. It will be shown that applying Arabic linguistic rules together with arithmetic operations succeeded in extracting numerical data from Arabic unstructured text with high accuracy reaches to 100%.</span></span>

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Domain-specific entity extraction from noisy, unstructured data using ontology-guided search

International Journal on Document Analysis and Recognition (IJDAR) ◽

10.1007/s10032-011-0149-5 ◽

2011 ◽

Vol 14 (2) ◽

pp. 201-211 ◽

Cited By ~ 2

Author(s):

Sergey Bratus ◽

Anna Rumshisky ◽

Alexy Khrabrov ◽

Rajenda Magar ◽

Paul Thompson

Keyword(s):

Unstructured Data ◽

Entity Extraction ◽

Guided Search ◽

Domain Specific

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Using Semantic Entity Extraction Method for a New Application

International Journal of Machine Learning and Computing ◽

10.7763/ijmlc.2012.v2.109 ◽

2012 ◽

pp. 178-182 ◽

Cited By ~ 4

Author(s):

Farhad Abedini ◽

Fariborz Mahmoudi ◽

Seyedeh Masoumeh Mirhashem

Keyword(s):

Extraction Method ◽

Entity Extraction

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A Named Entity Extraction Method for Commonly Used Steel Knowledge Graph

10.1007/978-981-16-6320-8_74 ◽

2021 ◽

pp. 724-732

Author(s):

Zeqi Ma ◽

Lingwei Ma ◽

Dongmei Fu ◽

Guangxuan Song ◽

Dawei Zhang

Keyword(s):

Extraction Method ◽

Knowledge Graph ◽

Entity Extraction ◽

Named Entity ◽

Named Entity Extraction

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Tibetan-Chinese Named Entity Extraction Based on Comparable Corpus

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.571-572.1202 ◽

2014 ◽

Vol 571-572 ◽

pp. 1202-1205

Author(s):

Yuan Sun ◽

Qian Zhao

Keyword(s):

Extraction Method ◽

Named Entity Recognition ◽

Sentence Length ◽

Entity Recognition ◽

Entity Extraction ◽

Named Entity ◽

Named Entity Extraction ◽

Cross Language Information Retrieval ◽

Cross Language ◽

Intersection Method

Tibetan-Chinese named entity extraction is the foundation of cross language information processing, and provides a basis for machine translation and cross language information retrieval research. In this paper, we use the multi-language links of Wikipedia to obtain Tibetan-Chinese comparable corpus, and combine sentence length, word matching and entity boundary words together to get parallel sentence. Then we extract Tibetan-Chinese named entity from the comparable corpus in three ways: (1) Extracting Natural labeling information. (2) Acquiring the links of Tibetan entries and Chinese entries. (3) Using sequence intersection method, which includes the sentence representation, Chinese named entity recognition and corresponding Tibetan sentences intersection. Finally, the results show the extraction method based on comparable corpus is effective.

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Entity Extraction from Unstructured Data on the Web

10.14264/uql.2015.9 ◽

2014 ◽

Author(s):

Tan Dat huynh

Keyword(s):

Unstructured Data ◽

Entity Extraction ◽

The Web

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Research on BERT-Based Audit Entity Extraction Method

10.1109/rcae53607.2021.9638834 ◽

2021 ◽

Author(s):

Rui Xiang ◽

Weibo Li ◽

Hua Yan

Keyword(s):

Extraction Method ◽

Entity Extraction

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Evaluation of the dark field method for large association of spread DNA

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100081814 ◽

1978 ◽

Vol 36 (2) ◽

pp. 190-191

Author(s):

Douglas C. Barker

Keyword(s):

Electron Microscopy ◽

Molecular Weight ◽

Mitochondrial Dna ◽

Extraction Method ◽

Field Method ◽

Dark Field ◽

Kinetoplast Dna ◽

Field Electron ◽

Field Electron Microscopy ◽

Dark Field Electron

A number of satisfactory methods are available for the electron microscopy of nicleic acids. These methods concentrated on fragments of nuclear, viral and mitochondrial DNA less than 50 megadaltons, on denaturation and heteroduplex mapping (Davies et al 1971) or on the interaction between proteins and DNA (Brack and Delain 1975). Less attention has been paid to the experimental criteria necessary for spreading and visualisation by dark field electron microscopy of large intact issociations of DNA. This communication will report on those criteria in relation to the ultrastructure of the (approx. 1 x 10-14g) DNA component of the kinetoplast from Trypanosomes. An extraction method has been developed to eliminate native endonucleases and nuclear contamination and to isolate the kinetoplast DNA (KDNA) as a compact network of high molecular weight. In collaboration with Dr. Ch. Brack (Basel [nstitute of Immunology), we studied the conditions necessary to prepare this KDNA Tor dark field electron microscopy using the microdrop spreading technique.

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