Mining Text Data: Special Features and Patterns

Delgado, Miguel; Martín-Bautista, María J.; Sánchez, Daniel; Miranda, María Amparo Vila

doi:10.1007/3-540-45728-3_11

Cited by 36 publications

(17 citation statements)

References 28 publications

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“…These two aspects are based on the fact that a scientific text is the result of cognitive and communicative activities of the certain subject in a scientific domain aimed at a specific objectfacts and processes of actual reality. The structure of a scientific text reflects the main components of a human scientific cognitive activity and contains the scientific knowledge as its product, such text can be used in the processes of data and information mining (Delgado et al, 2002). The textual data are not unstructured and a scientific text has a very complex implicit structure and is the source for solving the problem of the Knowledge Discovery in Texts (Feldman, Dogan 1995).…”

Section: Scientific Knowledge Presentationmentioning

confidence: 99%

“…Only after a step-by-step process a scientific idea is finally organized in the text form. Both semantic structure and composition of the text correlate with these cognition stages (Delgado et al, 2002).…”

Section: Scientific Knowledge Presentationmentioning

confidence: 99%

“…The patterns a particular text follows the nominations used for the object of the study, a representation of real world and subjective reality is related to knowledge representation (Delgado et al, 2002). Noun phrases as the terminology items are the objects of special research in both theoretical and applied aspects.…”

Section: Scientific Knowledge Presentationmentioning

confidence: 99%

See 2 more Smart Citations

On Methodology of Knowledge Presentation: Terms and Translation in Seismic Domain

Beliaeva¹,

Beliaeva²,

Chernyavskaya³

2016

J. Sib. Fed. Univ., Humanit. soc. sci.

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The underlying assumption of the paper is that the text is the result of information transfer and the source (starting point) o of information mining and extraction. Thereafter the scientific text content is universal and can be extracted in case of minimum coincidence of the author's and recipient's thesauri. In text translation the proper information extraction is determined with correct interpretation of terms/objects names. The paper focuses that adequacy of text perception and understanding on the lexical level is dictated by the text saturation with noun phrases, the degree of their compression and / or completeness of object nominations and their proper translations based on adequate bilingual dictionaries. Text translation in such a hazardous domain as aseismic construction is a crucial point in information exchange

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Section: Scientific Knowledge Presentationmentioning

confidence: 99%

Section: Scientific Knowledge Presentationmentioning

confidence: 99%

See 1 more Smart Citation

On Methodology of Knowledge Presentation: Terms and Translation in Seismic Domain

Beliaeva¹,

Beliaeva²,

Chernyavskaya³

2016

J. Sib. Fed. Univ., Humanit. soc. sci.

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“…To enhance the data mining process, scientist in both the academia and industry are beginning to explore the best methodologies that can aid in the unstructured data mining process; especially in the context of textual data mining. As a result, we have witnessed some methodologies such as: Information Retrieval algorithms based on templates (Hsu and Yih, 1997), association rules (Delgado et al, 2002;Zhao and Bhowmick, 2003), topic tracking and topic maps (Abramowicz et al, 2003(Abramowicz et al, /2004, term crawling (terms) (Janet and Reddy, 2011), document clustering (Han et al, 2010), document summarisation (Dey and Haque, 2009), Helmholtz search principle (Balinsky et al, 2010), re-usable dictionaries (Godbole et al, 2010), and so on.…”

Section: Unstructured Data Miningmentioning

confidence: 99%

Analytics-as-a-service framework for terms association mining in unstructured data

Lomotey

Deters

2014

IJBPIM

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Today's high-dimensional data, which is mostly unstructured, makes data patterns discovery (a.k.a. data mining) challenging and difficult for services engineers. Unstructured data mining deviates from existing information extraction methodologies that have been previously put forward due to the fact that recent data formation and storage has no standard schema; and the data is heterogeneous. While the topic is receiving significant attention recently from both the industry and academia, in this work, we aim at performing term association mining from distributed unstructured data storages. To achieve this goal, an analytics-as-a-service (AaaS) framework is proposed that theoretically relies on the Bernoulli algorithm to ensure the accurate determination association between terms. Specifically, the tool is applied to document-oriented data storages where the CouchDB data storage is employed for testing. The pilot evaluation of the proposed AaaS framework for the extraction of mining medical terms shows high accuracy and reliability regarding association maps.

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“…For further refinement in data stop words can be removed from this set of words. The second approach is Keywords / index data approach (Delgado, Martín-Bautista, Sánchez, & Vila, 2002;Feldman, Dagan, & Hirsh, 1998;Feldman & Hirsh, 1996).…”

Section: Text Preprocessingmentioning

confidence: 99%

From text mining to knowledge mining: An integrated framework of concept extraction and categorization for domain ontology

Andleeb¹

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Mining Text Data: Special Features and Patterns

Cited by 36 publications

References 28 publications

On Methodology of Knowledge Presentation: Terms and Translation in Seismic Domain

On Methodology of Knowledge Presentation: Terms and Translation in Seismic Domain

Analytics-as-a-service framework for terms association mining in unstructured data

From text mining to knowledge mining: An integrated framework of concept extraction and categorization for domain ontology

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