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Article
Publication date: 6 April 2012

Chengzhi Zhang and Dan Wu

Terminology is the set of technical words or expressions used in specific contexts, which denotes the core concept in a formal discipline and is usually applied in the…

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Abstract

Purpose

Terminology is the set of technical words or expressions used in specific contexts, which denotes the core concept in a formal discipline and is usually applied in the fields of machine translation, information retrieval, information extraction and text categorization, etc. Bilingual terminology extraction plays an important role in the application of bilingual dictionary compilation, bilingual ontology construction, machine translation and cross‐language information retrieval etc. This paper aims to address the issues of monolingual terminology extraction and bilingual term alignment based on multi‐level termhood.

Design/methodology/approach

A method based on multi‐level termhood is proposed. The new method computes the termhood of the terminology candidate as well as the sentence that includes the terminology by the comparison of the corpus. Since terminologies and general words usually have different distribution in the corpus, termhood can also be used to constrain and enhance the performance of term alignment when aligning bilingual terms on the parallel corpus. In this paper, bilingual term alignment based on termhood constraints is presented.

Findings

Experimental results show multi‐level termhood can get better performance than the existing method for terminology extraction. If termhood is used as a constraining factor, the performance of bilingual term alignment can be improved.

Originality/value

The termhood of the candidate terminology and the sentence that includes the terminology is used for terminology extraction, which is called multi‐level termhood. Multi‐level termhood is computed by the comparison of the corpus. Bilingual term alignment method based on termhood constraint is put forward and termhood is used in the task of bilingual terminology extraction. Experimental results show that termhood constraints can improve the performance of terminology alignment to some extent.

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Article
Publication date: 3 August 2021

Irvin Dongo, Yudith Cardinale, Ana Aguilera, Fabiola Martinez, Yuni Quintero, German Robayo and David Cabeza

This paper aims to perform an exhaustive revision of relevant and recent related studies, which reveals that both extraction methods are currently used to analyze…

Abstract

Purpose

This paper aims to perform an exhaustive revision of relevant and recent related studies, which reveals that both extraction methods are currently used to analyze credibility on Twitter. Thus, there is clear evidence of the need of having different options to extract different data for this purpose. Nevertheless, none of these studies perform a comparative evaluation of both extraction techniques. Moreover, the authors extend a previous comparison, which uses a recent developed framework that offers both alternates of data extraction and implements a previously proposed credibility model, by adding a qualitative evaluation and a Twitter-Application Programming Interface (API) performance analysis from different locations.

Design/methodology/approach

As one of the most popular social platforms, Twitter has been the focus of recent research aimed at analyzing the credibility of the shared information. To do so, several proposals use either Twitter API or Web scraping to extract the data to perform the analysis. Qualitative and quantitative evaluations are performed to discover the advantages and disadvantages of both extraction methods.

Findings

The study demonstrates the differences in terms of accuracy and efficiency of both extraction methods and gives relevance to much more problems related to this area to pursue true transparency and legitimacy of information on the Web.

Originality/value

Results report that some Twitter attributes cannot be retrieved by Web scraping. Both methods produce identical credibility values when a robust normalization process is applied to the text (i.e. tweet). Moreover, concerning the time performance, Web scraping is faster than Twitter API and it is more flexible in terms of obtaining data; however, Web scraping is very sensitive to website changes. Additionally, the response time of the Twitter API is proportional to the distance from the central server at San Francisco.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

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Article
Publication date: 9 August 2021

Xintong Zhao, Jane Greenberg, Vanessa Meschke, Eric Toberer and Xiaohua Hu

The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including…

Abstract

Purpose

The output of academic literature has increased significantly due to digital technology, presenting researchers with a challenge across every discipline, including materials science, as it is impossible to manually read and extract knowledge from millions of published literature. The purpose of this study is to address this challenge by exploring knowledge extraction in materials science, as applied to digital scholarship. An overriding goal is to help inform readers about the status knowledge extraction in materials science.

Design/methodology/approach

The authors conducted a two-part analysis, comparing knowledge extraction methods applied materials science scholarship, across a sample of 22 articles; followed by a comparison of HIVE-4-MAT, an ontology-based knowledge extraction and MatScholar, a named entity recognition (NER) application. This paper covers contextual background, and a review of three tiers of knowledge extraction (ontology-based, NER and relation extraction), followed by the research goals and approach.

Findings

The results indicate three key needs for researchers to consider for advancing knowledge extraction: the need for materials science focused corpora; the need for researchers to define the scope of the research being pursued, and the need to understand the tradeoffs among different knowledge extraction methods. This paper also points to future material science research potential with relation extraction and increased availability of ontologies.

Originality/value

To the best of the authors’ knowledge, there are very few studies examining knowledge extraction in materials science. This work makes an important contribution to this underexplored research area.

Details

The Electronic Library , vol. 39 no. 3
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 7 July 2020

Pei Ni Chuah, Dhalini Nyanasegaram, Ke-Xin Yu, Rasny Mohamed Razik, Samer Al-Dhalli, Chin Siang Kue, Khozirah Shaari and Chean Hui Ng

The purpose of this paper is to evaluate the antioxidant activity and toxicity of Clinacanthus nutans leaves from three conventional extraction methods, i.e. maceration…

Abstract

Purpose

The purpose of this paper is to evaluate the antioxidant activity and toxicity of Clinacanthus nutans leaves from three conventional extraction methods, i.e. maceration, Soxhlet and magnetic stirring.

Design/methodology/approach

Total flavonoid content (TFC) and phenolic content (TPC) were determined using colorimetric method of aluminum chloride and Folin-Ciocalteu (FC) assay, respectively. Antioxidant property of C. nutans was evaluated using 2,2'-diphenyl-1-pierylhydrazyl (DPPH) free radical scavenging assay. Cytotoxic activity of C. nutans against brine shrimp was evaluated based on LC50 (lethality concentration) after 24 h exposure to the plant extract.

Findings

The highest TPC of C. nutans was observed with Soxhlet extraction method (98.87 ± 10.43 mg of gallic acid equivalents (GAE/g) followed by maceration (68.77 ± 2.45 mg of GAE/g) and magnetic stirring (46.75 ± 2.45 mg of GAE/g). Interestingly, remarkable highest TFC was observed with magnetic stirring (568.90 ± 4.85 mg of rutin equivalent (RE)/g) followed by maceration (249.60 ± 2.79 mg of RE/g) and Soxhlet (174.8 ± 1.74 mg of RE/g). On the other hands, the extract obtained using maceration method showed the highest antioxidant activity (IC50: 14.18 mg/mL compared to ascorbic acid 144.36 µg/mL). Cytotoxicity of C. nutans from all extraction methods showed similar LC50 values with maceration (3.81 mg/mL), Soxhlet (2.61 mg/mL) and magnetic stirring (4.56 mg/mL), respectively.

Originality/value

Both phenolic and flavonoids are responsible for the antioxidant activity, of C. nutans extracts. Based on Meyer's toxicity index, all extracts were nontoxic (LC50>1 mg/mL).

Details

British Food Journal, vol. 122 no. 10
Type: Research Article
ISSN: 0007-070X

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Article
Publication date: 11 September 2017

Saheed Adewale Omoniyi, Michael Ayodele Idowu, Abiodun Aderoju Adeola and Adekunle Ayodeji Folorunso

This paper aims to review the chemical composition and industrial benefits of oil extracted from dikanut kernels.

Abstract

Purpose

This paper aims to review the chemical composition and industrial benefits of oil extracted from dikanut kernels.

Design/methodology/approach

Several literatures on chemical composition of dikanut kernels, methods of oil extraction from dikanut kernels and chemical composition of oil extracted from dikanut kernels were critically reviewed.

Findings

The review showed that proximate composition of dikanut kernels ranged from 2.10 to 11.90 per cent, 7.70 to 9.24 per cent, 51.32 to 70.80 per cent, 0.86 to 10.23 per cent, 2.26 to 6.80 per cent and 10.72 to 26.02 per cent for moisture, crude protein, crude fat, crude fibre, ash and carbohydrate contents, respectively. The methods of oil extraction from dikanut kernels include soxhlet extraction method, novel extraction method, enzymatic extraction method and pressing method. The quality attributes of dikanut kernel oil ranged from 1.59 to 4.70 g/100g, 0.50 to 2.67 meq/Kg, 4.30 to 13.40 g/100g, 187.90 to 256.50 mg KOH/g and 3.18 to 12.94 mg KOH/g for free fatty acid, peroxide value, iodine value, saponification value and acid value, respectively. Also, the percentage compositions of oleic, myristic, stearic, linolenic, palmitic, lauric, saturated fatty acids, monosaturated fatty acids and polyunsaturated fatty acids ranging from 0.00 to 6.90, 20.50 to 61.68, 0.80 to 11.40, 0.27 to 6.40, 5.06 to 10.30, 27.63 to 40.70, 97.45 to 98.73, 1.82 to 2.12 and 0.27 to 0.49 respectively. The results showed that dikanut kernels has appreciable amount of protein, carbohydrate and high level of fat content while oil extracted from dikanut kernels have high saponification value, high myristic acid and high lauric acid.

Research limitations/implications

There are scanty information/published works on industrial products made from oil extracted from dikanut kernels.

Practical implications

The review helps in identifying different methods of extraction of oil from dikanut kernels apart from popular soxhlet extraction method (uses of organic solvent). Also, it helps to identify the domestic and industrial benefits of oil extracted from dikanut kernels.

Originality/value

The review showed that oil extracted from dikanut kernels could be useful as food additive, flavour ingredient, coating fresh citrus fruits and in the manufacture of margarine, oil creams, cooking oil, defoaming agent, cosmetics and pharmaceutical products.

Details

Nutrition & Food Science, vol. 47 no. 5
Type: Research Article
ISSN: 0034-6659

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Article
Publication date: 26 October 2018

Satakshi Aggarwal and Tanu Jain

Modern thermal and non-thermal pretreatment techniques, namely, enzymatic treatment, gas phase plasma treatment and ohmic heating have become more pronounced over…

Abstract

Purpose

Modern thermal and non-thermal pretreatment techniques, namely, enzymatic treatment, gas phase plasma treatment and ohmic heating have become more pronounced over conventional techniques for enhanced coloured phytochemicals (pigments) extraction. Presently, numbers of pretreatment techniques are available with some unique feature. It is difficult to choose best pretreatment method to be employed for phytochemicals extraction from different sources. Therefore, this paper aims to discuss different modern pretreatment techniques for extraction with their potential results over conventional techniques.

Design/methodology/approach

Research and review articles targeting to the thermal and non-thermal pretreatment techniques were collected from Google Scholar. The required information has been tabulated and discussed which included qualities of modern pretreatment techniques over conventional techniques, phytochemical extraction and best pretreatment methods for optimized results.

Findings

Every pre-treatment has its own advantages and disadvantages for a particular phytochemical and its extraction from various sources. Enzymes can be used in combinations to enhance final yield like extraction of carotenoids (pectinase, cellulase and hemicellulase) from chillies and lycopene (pectinase and cellulase) from tomato. Utilization of each method depends upon many factors such as source of pigment, cost and energy consumption. CO2 pretreatment gives good results for carotenoid extraction from algae sources. Ohmic heating can yield high anthocyanin content. Modifications in conventional blanching has reduced final waste and improvised the properties of pigment.

Originality/value

This study comprises collective information regarding modern pre-treatment for extraction over conventional pre-treatments. The study also covers future trends and certain new hybrid approaches which are still less flourished.

Details

Nutrition & Food Science, vol. 49 no. 3
Type: Research Article
ISSN: 0034-6659

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Article
Publication date: 24 June 2020

Yilu Zhou and Yuan Xue

Strategic alliances among organizations are some of the central drivers of innovation and economic growth. However, the discovery of alliances has relied on pure manual…

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142

Abstract

Purpose

Strategic alliances among organizations are some of the central drivers of innovation and economic growth. However, the discovery of alliances has relied on pure manual search and has limited scope. This paper proposes a text-mining framework, ACRank, that automatically extracts alliances from news articles. ACRank aims to provide human analysts with a higher coverage of strategic alliances compared to existing databases, yet maintain a reasonable extraction precision. It has the potential to discover alliances involving less well-known companies, a situation often neglected by commercial databases.

Design/methodology/approach

The proposed framework is a systematic process of alliance extraction and validation using natural language processing techniques and alliance domain knowledge. The process integrates news article search, entity extraction, and syntactic and semantic linguistic parsing techniques. In particular, Alliance Discovery Template (ADT) identifies a number of linguistic templates expanded from expert domain knowledge and extract potential alliances at sentence-level. Alliance Confidence Ranking (ACRank)further validates each unique alliance based on multiple features at document-level. The framework is designed to deal with extremely skewed, noisy data from news articles.

Findings

In evaluating the performance of ACRank on a gold standard data set of IBM alliances (2006–2008) showed that: Sentence-level ADT-based extraction achieved 78.1% recall and 44.7% precision and eliminated over 99% of the noise in news articles. ACRank further improved precision to 97% with the top20% of extracted alliance instances. Further comparison with Thomson Reuters SDC database showed that SDC covered less than 20% of total alliances, while ACRank covered 67%. When applying ACRank to Dow 30 company news articles, ACRank is estimated to achieve a recall between 0.48 and 0.95, and only 15% of the alliances appeared in SDC.

Originality/value

The research framework proposed in this paper indicates a promising direction of building a comprehensive alliance database using automatic approaches. It adds value to academic studies and business analyses that require in-depth knowledge of strategic alliances. It also encourages other innovative studies that use text mining and data analytics to study business relations.

Details

Information Technology & People, vol. 33 no. 5
Type: Research Article
ISSN: 0959-3845

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Article
Publication date: 18 June 2019

Rashidi Othman, Mohd Akram Abdurasid, Noraini Mahmad and Nurrulhidayah Ahmad Fadzillah

The purpose of this paper is to extract, characterise and quantify curcumin from selected Zingiberaceae of “kunyit” or turmeric (Curcuma longa), “temu lawak” or Javanese…

Abstract

Purpose

The purpose of this paper is to extract, characterise and quantify curcumin from selected Zingiberaceae of “kunyit” or turmeric (Curcuma longa), “temu lawak” or Javanese turmeric (Curcuma xanthorrhiza), “temu pauh” (Curcuma mangga), “lempoyang” (Zingiber zerumbet) and “bonglai” (Zingiber cassumunar) using alkaline and chemical-based extraction method for antimicrobial and antioxidant activities.

Design/methodology/approach

Through the alkaline-based extraction method, all parts of rhizome samples were freeze-dried for 72 h before grounded into a fine powder and kept at −20°C. The powdered sample (0.1 g) was weighed and placed in a 50 mL tube. About 20 mL of 2 M NaOH solution was added into the tube. The solution was allowed to stand for 30 min. Then, 20 mL of ethyl acetate was added into the tube. The solution was mixed well then centrifuged at 13,500 rpm for 3 min. The upper layer was collected using a pipette. The process was repeated until the upper layer became almost colourless. The collected ethyl acetate solution was concentrated using a rotary evaporator to remove the ethyl acetate from the extracted compound. The concentrated curcumin was placed in a universal bottle, which was then dried from the remaining ethyl acetate using nitrogen drying process. The dried curcumin was then stored inside the freezer at −20ºC. The antimicrobial activities were using agar diffusion method against bacterial and fungi, while the antioxidant activity was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging assay.

Findings

All the samples successfully showed a single peak (curcumin) that gained from the high-performance liquid chromatography (HPLC) chromatogram analysis (at 425 nm) using the alkaline-based extraction method and the highest curcumin content was in turmeric (12.95 ± 1.07mg/g DW). At 10.0 mg/mL curcumin concentration, the best antibacterial activity was against on methicillin-resistant staphylococcus aureus (MRSA) with 7.50 ± 0.71 mm inhibition zone, while the best antifungal activity was against on Aspergillus niger with 8.00 ± 0.41 mm inhibition zone. The DPPH antioxidant test resulted in the highest inhibition (110.41 per cent) was at 0.25 mg/mL curcumin concentration.

Originality/value

Through HPLC analysis, all samples successfully showed a single peak of curcumin at 425 nm. The total carotenoid determination from turmeric revealed that the samples content was substantially higher using alkaline-based extraction (18.40 ± 0.07 mg/g DW) compared to chemical-based extraction (9.42 ± 0.20 mg/g ± SD).

Details

Pigment & Resin Technology, vol. 48 no. 4
Type: Research Article
ISSN: 0369-9420

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Article
Publication date: 11 January 2021

Mingyang Li, Zhijiang Du, Xiaoxing Ma, Wei Dong, Yongzhi Wang, Yongzhuo Gao and Wei Chen

This paper aims to propose a robotic automation system for processing special-shaped thin-walled workpieces, which includes a measurement part and a processing part.

Abstract

Purpose

This paper aims to propose a robotic automation system for processing special-shaped thin-walled workpieces, which includes a measurement part and a processing part.

Design/methodology/approach

In the measurement part, to efficiently and accurately realize the three-dimensional camera hand-eye calibration based on a large amount of measurement data, this paper improves the traditional probabilistic method. To solve the problem of time-consuming in the extraction of point cloud features, this paper proposes a point cloud feature extraction method based on seed points. In the processing part, the authors design a new type of chamfering tool. During the process, the robot adopts admittance control to perform compensation according to the feedback of four sensors mounted on the tool.

Findings

Experiments show that the proposed system can make the tool smoothly fit the chamfered edge during processing and the machined chamfer meets the processing requirements of 0.5 × 0.5 to 0.9 × 0.9 mm2.

Practical implications

The proposed design and approach can be applied on many types of special-shaped thin-walled parts. This will give a new solution for the automation integration problem in aerospace manufacturing.

Originality/value

A novel robotic automation system for processing special-shaped thin-walled workpieces is proposed and a new type of chamfering tool is designed. Furthermore, a more accurate probabilistic hand-eye calibration method and a more efficient point cloud extraction method are proposed, which are suitable for this system when comparing with the traditional methods.

Details

Assembly Automation, vol. 41 no. 1
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 2 December 2020

Yohanes Sigit Purnomo W.P., Yogan Jaya Kumar and Nur Zareen Zulkarnain

Extracting information from unstructured data becomes a challenging task for computational linguistics. Public figure’s statement attributed by journalists in a story is…

Abstract

Purpose

Extracting information from unstructured data becomes a challenging task for computational linguistics. Public figure’s statement attributed by journalists in a story is one type of information that can be processed into structured data. Therefore, having the knowledge base about this data will be very beneficial for further use, such as for opinion mining, claim detection and fact-checking. This study aims to understand statement extraction tasks and the models that have already been applied to formulate a framework for further study.

Design/methodology/approach

This paper presents a literature review from selected previous research that specifically addresses the topics of quotation extraction and quotation attribution. Research works that discuss corpus development related to quotation extraction and quotation attribution are also considered. The findings of the review will be used as a basis for proposing a framework to direct further research.

Findings

There are three findings in this study. Firstly, the extraction process still consists of two main tasks, namely, the extraction of quotations and the attribution of quotations. Secondly, most extraction algorithms rely on a rule-based algorithm or traditional machine learning. And last, the availability of corpus, which is limited in quantity and depth. Based on these findings, a statement extraction framework for Indonesian language corpus and model development is proposed.

Originality/value

The paper serves as a guideline to formulate a framework for statement extraction based on the findings from the literature study. The proposed framework includes a corpus development in the Indonesian language and a model for public figure statement extraction. Furthermore, this study could be used as a reference to produce a similar framework for other languages.

Details

Global Knowledge, Memory and Communication, vol. 70 no. 6/7
Type: Research Article
ISSN: 2514-9342

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