Grammar checking and relation extraction in text: approaches, techniques and open challenges

2019 ◽  
Vol 53 (3) ◽  
pp. 373-394
Author(s):  
Nora Madi ◽  
Rawan Al-Matham ◽  
Hend Al-Khalifa
Keyword(s):  
Error Detection ◽  
Relation Extraction ◽  
Knowledge Bases ◽  
Automatic Extraction ◽  
Data Sets ◽  
Future Directions ◽  
Content Type ◽  
Author Identification ◽  
Searching Strategy ◽  
Research Questions

Purpose The purpose of this paper is to provide an overall review of grammar checking and relation extraction (RE) literature, their techniques and the open challenges associated with them; and, finally, suggest future directions. Design/methodology/approach The review on grammar checking and RE was carried out using the following protocol: we prepared research questions, planed for searching strategy, addressed paper selection criteria to distinguish relevant works, extracted data from these works, and finally, analyzed and synthesized the data. Findings The output of error detection models could be used for creating a profile of a certain writer. Such profiles can be used for author identification, native language identification or even the level of education, to name a few. The automatic extraction of relations could be used to build or complete electronic lexical thesauri and knowledge bases. Originality/value Grammar checking is the process of detecting and sometimes correcting erroneous words in the text, while RE is the process of detecting and categorizing predefined relationships between entities or words that were identified in the text. The authors found that the most obvious challenge is the lack of data sets, especially for low-resource languages. Also, the lack of unified evaluation methods hinders the ability to compare results.

Consumer confusion: a systematic review and research directions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vishakha Chauhan ◽  
Mahim Sagar
Keyword(s):  
Conceptual Framework ◽  
Design Methodology ◽  
Important Research ◽  
Research Gaps ◽  
Future Directions ◽  
Research Directions ◽  
Content Type ◽  
Marketing Literature ◽  
Consumer Confusion ◽  
Research Questions

Purpose The purpose of this paper is to systematically review and analyse extant marketing literature on consumer confusion to propose an integrated conceptual framework and highlight important research gaps. Design/methodology/approach Systematic literature review methodology was followed for article selection. Selected articles were subjected to content analysis to derive thematic as well as descriptive results. Findings Antecedents, consequences, moderators, mediators and application of the construct in the different contexts have been reported. An integrated framework along with research questions and future directions has also been proposed. Originality/value To the best of the authors’ knowledge, this study is notably the first attempt to systematically review the marketing literature on consumer confusion. The conceptual framework and proposed research questions create a research agenda around the problem of consumer confusion and contribute towards the advancement of extant literature.

Viewing marketing through entrepreneurial mindset: a systematic review

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anshita Yadav ◽  
Sanchita Bansal
Keyword(s):  
Customer Orientation ◽  
Research Papers ◽  
Future Directions ◽  
Content Type ◽  
Entrepreneurial Marketing ◽  
Marketing Innovation ◽  
Extant Literature ◽  
Research Designs ◽  
Research Questions ◽  
Methodological Approaches

PurposeThe present paper explores and analyses various aspects of entrepreneurial marketing in the different regions (developed or developing) and attempts to consolidate the extant literature in the field of entrepreneurial marketing and suggests future directions for research.Design/methodology/approachThe research questions developed by the paper deal with (1) comparison of entrepreneurial marketing in the developed and developing world; (2) methodological approaches used in entrepreneurial marketing; (3) the constructs or theories used in literature; (4) the existing research gaps and potential future directions in research of entrepreneurial marketing. To answer the same, we conduct a systematic literature review of the 82 research papers extracted from the Web of Science (WoS) and ScienceDirect databases.FindingsThe findings are presented in the form of descriptive and results. The descriptive findings show that more studies are needed in developing nations, introducing or developing entrepreneurial marketing conceptually, using mixed research designs, having objective measurements of constructs and contributing to comparative studies. The results discuss the constructs and theories employed in the extant literature and suggest that theories like human capital, creation, causation or trust are fundamental to study entrepreneurial marketing.Originality/valueThe paper adopts the existing entrepreneurial, marketing, innovation, and customer orientation (EMICO) framework and further develops an organizing framework to discover several gaps in the existing literature that can further be explored and promote the development of research in entrepreneurial marketing.

Corruption crime and punishment: evidence from China’s state corruption audits

2017 ◽  
Vol 24 (4) ◽  
pp. 601-619 ◽  
Author(s):  
Guangyou Liu ◽  
Siyu Liu
Keyword(s):  
Financial Crime ◽  
Data Sets ◽  
Content Type ◽  
Organizational Corruption ◽  
State Audit ◽  
Central Commission ◽  
Administrative Change ◽  
Research Questions ◽  
Criminal Penalties ◽  
Crime Literature

Purpose This paper aims to answer the following two research questions: Do corruption cases present different features before and since the new administration in China? How are criminal penalties affected by these corruption features? Design/methodology/approach The investigation is based on the online disclosure of 269 state corruption audits and their consequences, which have been made public by China’s National Audit Office since 2011. By manual coding, these official reports were analyzed, and an appropriate-sized sample of corruption cases was chosen. The authors then adopted Welch’s t-test and regression model methods to test the research hypotheses relevant to the two research questions. Findings The authors find that larger embezzlement or bribery amounts and more organizational corruption cases have been detected and punished since the anti-corruption campaign was launched by the new administration. They also conclude that significantly tougher criminal penalties were given to corruption cases involving large monetary amounts, that bribery cases were more harshly punished compared to other occupational crimes and that individual perpetrators received tougher criminal penalties than organizational criminals. In addition, the authors observe a trend that criminal penalties for corruption have been increasingly harsher in recent years. Research limitations/implications The limitations of this study are quite clear as the Chinese corruption cases in this sample only include state corruption audit cases and does not refer to high-profile corruption cases investigated by the Central Commission of Discipline Inspection. However, this study suggests that state corruption audit results are a good research sample, which can be used to extend empirical tests to archival data acquired from state audit practices and can encourage more studies on public sector auditing and occupational financial crime. Practical implications State corruption audits can be an effective approach to successful anti-corruption campaigns, and the conclusions can be useful to policy makers and legislators in China and other developing countries. Originality/value This paper bridges some gaps in the existing financial crime literature. First, this study on corruption features is located within the context of a political administrative change; second, the state audit is highlighted as a supervising agency in the anti-corruption campaign; and third, the authors’ contribution adds to the empirical testing of data sets of state corruption audits within the existing financial crime literature.

Ranking authors in academic social networks: a survey

2018 ◽  
Vol 36 (1) ◽  
pp. 97-128 ◽  
Author(s):  
Tehmina Amjad ◽  
Ali Daud ◽  
Naif Radi Aljohani
Keyword(s):  
Social Networks ◽  
Design Methodology ◽  
Data Sets ◽  
Ranking Problem ◽  
Future Directions ◽  
Content Type ◽  
Evaluation Measures ◽  
Pros And Cons ◽  
Author Ranking ◽  
Academic Social Networks

Purpose This study reviews the methods found in the literature for the ranking of authors, identifies the pros and cons of these methods, discusses and compares these methods. The purpose of this paper is to study is to find the challenges and future directions of ranking of academic objects, especially authors, for future researchers. Design/methodology/approach This study reviews the methods found in the literature for the ranking of authors, classifies them into subcategories by studying and analyzing their way of achieving the objectives, discusses and compares them. The data sets used in the literature and the evaluation measures applicable in the domain are also presented. Findings The survey identifies the challenges involved in the field of ranking of authors and future directions. Originality/value To the best of the knowledge, this is the first survey that studies the author ranking problem in detail and classifies them according to their key functionalities, features and way of achieving the objective according to the requirement of the problem.

Stereotactic radiation treatment planning and follow-up studies involving fused multimodality imaging

2004 ◽  
Vol 101 (Supplement3) ◽  
pp. 326-333 ◽  
Author(s):  
Klaus D. Hamm ◽  
Gunnar Surber ◽  
Michael Schmücking ◽  
Reinhard E. Wurm ◽  
Rene Aschenbach ◽  
...  
Keyword(s):  
Image Fusion ◽  
Treatment Planning ◽  
Radiation Treatment ◽  
Data Sets ◽  
Slice Thickness ◽  
Radiation Treatment Planning ◽  
Content Type ◽  
Follow Up Studies ◽  
Fine Print

Object. Innovative new software solutions may enable image fusion to produce the desired data superposition for precise target definition and follow-up studies in radiosurgery/stereotactic radiotherapy in patients with intracranial lesions. The aim is to integrate the anatomical and functional information completely into the radiation treatment planning and to achieve an exact comparison for follow-up examinations. Special conditions and advantages of BrainLAB's fully automatic image fusion system are evaluated and described for this purpose. Methods. In 458 patients, the radiation treatment planning and some follow-up studies were performed using an automatic image fusion technique involving the use of different imaging modalities. Each fusion was visually checked and corrected as necessary. The computerized tomography (CT) scans for radiation treatment planning (slice thickness 1.25 mm), as well as stereotactic angiography for arteriovenous malformations, were acquired using head fixation with stereotactic arc or, in the case of stereotactic radiotherapy, with a relocatable stereotactic mask. Different magnetic resonance (MR) imaging sequences (T1, T2, and fluid-attenuated inversion-recovery images) and positron emission tomography (PET) scans were obtained without head fixation. Fusion results and the effects on radiation treatment planning and follow-up studies were analyzed. The precision level of the results of the automatic fusion depended primarily on the image quality, especially the slice thickness and the field homogeneity when using MR images, as well as on patient movement during data acquisition. Fully automated image fusion of different MR, CT, and PET studies was performed for each patient. Only in a few cases was it necessary to correct the fusion manually after visual evaluation. These corrections were minor and did not materially affect treatment planning. High-quality fusion of thin slices of a region of interest with a complete head data set could be performed easily. The target volume for radiation treatment planning could be accurately delineated using multimodal information provided by CT, MR, angiography, and PET studies. The fusion of follow-up image data sets yielded results that could be successfully compared and quantitatively evaluated. Conclusions. Depending on the quality of the originally acquired image, automated image fusion can be a very valuable tool, allowing for fast (∼ 1–2 minute) and precise fusion of all relevant data sets. Fused multimodality imaging improves the target volume definition for radiation treatment planning. High-quality follow-up image data sets should be acquired for image fusion to provide exactly comparable slices and volumetric results that will contribute to quality contol.

Mean reversion in corporate leverage: evidence from India

2019 ◽  
Vol 45 (9) ◽  
pp. 1183-1198
Author(s):  
Gaurav S. Chauhan ◽  
Pradip Banerjee
Keyword(s):  
Capital Structure ◽  
Emerging Market ◽  
Simulated Data ◽  
Mean Reversion ◽  
Developed Countries ◽  
Data Sets ◽  
Debt Ratio ◽  
Testing Strategy ◽  
Content Type ◽  
Financing Behavior

Purpose Recent papers on target capital structure show that debt ratio seems to vary widely in space and time, implying that the functional specifications of target debt ratios are of little empirical use. Further, target behavior cannot be adjudged correctly using debt ratios, as they could revert due to mechanical reasons. The purpose of this paper is to develop an alternative testing strategy to test the target capital structure. Design/methodology/approach The authors make use of a major “shock” to the debt ratios as an event and think of a subsequent reversion as a movement toward a mean or target debt ratio. By doing this, the authors no longer need to identify target debt ratios as a function of firm-specific variables or any other rigid functional form. Findings Similar to the broad empirical evidence in developed economies, there is no perceptible and systematic mean reversion by Indian firms. However, unlike developed countries, proportionate usage of debt to finance firms’ marginal financing deficits is extensive; equity is used rather sparingly. Research limitations/implications The trade-off theory could be convincingly refuted at least for the emerging market of India. The paper here stimulated further research on finding reasons for specific financing behavior of emerging market firms. Practical implications The results show that the firms’ financing choices are not only depending on their own firm’s specific variables but also on the financial markets in which they operate. Originality/value This study attempts to assess mean reversion in debt ratios in a unique but reassuring manner. The results are confirmed by extensive calibration of the testing strategy using simulated data sets.

Unmanned aerial vehicle reconnaissance image recognition based on convolutional neural network

2021 ◽  
pp. 1-10
Author(s):  
Lipeng Si ◽  
Baolong Liu ◽  
Yanfang Fu
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Image Recognition ◽  
Error Detection ◽  
Convolution Neural Network ◽  
Data Sets ◽  
Small Target ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Real Time Tracking

The important strategic position of military UAVs and the wide application of civil UAVs in many fields, they all mark the arrival of the era of unmanned aerial vehicles. At present, in the field of image research, recognition and real-time tracking of specific objects in images has been a technology that many scholars continue to study in depth and need to be further tackled. Image recognition and real-time tracking technology has been widely used in UAV aerial photography. Through the analysis of convolution neural network algorithm and the comparison of image recognition technology, the convolution neural network algorithm is improved to improve the image recognition effect. In this paper, a target detection technique based on improved Faster R-CNN is proposed. The algorithm model is implemented and the classification accuracy is improved through Faster R-CNN network optimization. Aiming at the problem of small target error detection and scale difference in aerial data sets, this paper designs the network structure of RPN and the optimization scheme of related algorithms. The structure of Faster R-CNN is adjusted by improving the embedding of CNN and OHEM algorithm, the accuracy of small target and multitarget detection is improved as a whole. The experimental results show that: compared with LENET-5, the recognition accuracy of the proposed algorithm is significantly improved. And with the increase of the number of samples, the accuracy of this algorithm is 98.9%.

Expanding knowledge frontiers in entrepreneurship: examining bricolage and effectuation

2020 ◽  
Vol 26 (5) ◽  
pp. 1043-1065
Author(s):  
Vanessa Vasconcelos Scazziota ◽  
Tales Andreassi ◽  
Fernando Antonio Ribeiro Serra ◽  
Luiz Guerrazzi
Keyword(s):  
Decision Process ◽  
Design Methodology ◽  
Knowledge Bases ◽  
Research Trends ◽  
Bibliographic Coupling ◽  
Content Type ◽  
Methodological Feature ◽  
Theoretical Approaches ◽  
And Behaviors ◽  
Opportunity Creation

PurposeOur purpose is to evaluate effectuation and bricolage through their unique and shared references to understand possible overlaps and conceptual complementarities between these theoretical approaches.Design/methodology/approachThe use of bibliometric techniques to examining simultaneously both theoretical approaches is one of the distinctions of this work. Another important methodological feature is the use of co-citation and bibliographic coupling and their interaction, to verify 179 published documents relating to their references.FindingsThe study reveals the intellectual structures underlying the approaches and differences originating from their knowledge bases, as well as the research trends.Originality/valueBy identifying the differences in the decision process and behaviors that culminate in opportunity creation in each, it offers a complementary vision of previous works. The evidence stresses it is interesting to explore their integration, considering the complementarity of their unique aspects.

The ingenious marketing of modern paintings

2014 ◽  
Vol 6 (2) ◽  
pp. 211-233
Author(s):  
Thomas M. Bayer ◽  
John Page
Keyword(s):  
Exchange Process ◽  
Art Market ◽  
Late Nineteenth Century ◽  
Data Sets ◽  
Content Type ◽  
Secondary Sources ◽  
Auction Houses ◽  
Art Dealers ◽  
The Media ◽  
Eighteenth And Nineteenth Centuries

Purpose – This paper aims to analyze the evolution of the marketing of paintings and related visual products from its nascent stages in England around 1700 to the development of the modern art market by 1900, with a brief discussion connecting to the present. Design/methodology/approach – Sources consist of a mixture of primary and secondary sources as well as a series of econometric and statistical analyses of specifically constructed and unique data sets that list nearly more than 50,000 different sales of paintings during this period. One set records sales of paintings at various English auction houses during the eighteenth and nineteenth centuries; the second set consists of all purchases and sales of paintings recorded in the stock books of the late nineteenth-century London art dealer, Arthur Tooth, during the years of 1870/1871. The authors interpret the data under a commoditization model first introduced by Igor Kopytoff in 1986 that posits that markets and their participants evolve toward maximizing the efficiency of their exchange process within the prevailing exchange technology. Findings – We found that artists were largely responsible for a series of innovations in the art market that replaced the prevailing direct relationship between artists and patron with a modern market for which painters produced works on speculation to be sold by enterprising middlemen to an anonymous public. In this process, artists displayed a remarkable creativity and a seemingly instinctive understanding of the principles of competitive marketing that should dispel the erroneous but persistent notion that artistic genius and business savvy are incompatible. Research limitations/implications – A similar marketing analysis could be done of the development of the art markets of other leading countries, such as France, Italy and Holland, as well as the current developments of the art market. Practical implications – The same process of the development of the art market in England is now occurring in Latin America and China. Also, the commoditization process continues in the present, now using the Internet and worldwide art dealers. Originality/value – This is the first article to trace the historical development of the marketing of art in all of its components: artists, dealers, artist organizations, museums, curators, art critics, the media and art historians.

Improving recommender systems’ performance on cold-start users and controversial items by a new similarity model

2016 ◽  
Vol 12 (2) ◽  
pp. 126-149 ◽  
Author(s):  
Masoud Mansoury ◽  
Mehdi Shajari
Keyword(s):  
Real World ◽  
Design Methodology ◽  
Cold Start ◽  
Selection Function ◽  
Data Sets ◽  
Real World Data ◽  
Content Type ◽  
User Similarity ◽  
Active User ◽  
Similarity Model

Purpose This paper aims to improve the recommendations performance for cold-start users and controversial items. Collaborative filtering (CF) generates recommendations on the basis of similarity between users. It uses the opinions of similar users to generate the recommendation for an active user. As a similarity model or a neighbor selection function is the key element for effectiveness of CF, many variations of CF are proposed. However, these methods are not very effective, especially for users who provide few ratings (i.e. cold-start users). Design/methodology/approach A new user similarity model is proposed that focuses on improving recommendations performance for cold-start users and controversial items. To show the validity of the authors’ similarity model, they conducted some experiments and showed the effectiveness of this model in calculating similarity values between users even when only few ratings are available. In addition, the authors applied their user similarity model to a recommender system and analyzed its results. Findings Experiments on two real-world data sets are implemented and compared with some other CF techniques. The results show that the authors’ approach outperforms previous CF techniques in coverage metric while preserves accuracy for cold-start users and controversial items. Originality/value In the proposed approach, the conditions in which CF is unable to generate accurate recommendations are addressed. These conditions affect CF performance adversely, especially in the cold-start users’ condition. The authors show that their similarity model overcomes CF weaknesses effectively and improve its performance even in the cold users’ condition.

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