Seongung Jo¹, Heung-Seon Oh^1,*, Sanghun Im¹, Gibaeg Kim¹, Seonho Kim²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2967-2980, 2023, DOI:10.32604/cmc.2023.031983

Abstract Analyzing Research and Development (R&D) trends is important because it can influence future decisions regarding R&D direction. In typical trend analysis, topic or technology taxonomies are employed to compute the popularities of the topics or codes over time. Although it is simple and effective, the taxonomies are difficult to manage because new technologies are introduced rapidly. Therefore, recent studies exploit deep learning to extract pre-defined targets such as problems and solutions. Based on the recent advances in question answering (QA) using deep learning, we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports. With the… More >

Kun Ding¹, Lu Xu², Ming Liu¹, Xiaoxiong Zhang¹, Liu Liu¹, Daojian Zeng^2,*, Yuting Liu^1,3, Chen Jin⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 641-654, 2023, DOI:10.32604/cmc.2023.031052

Abstract Event detection (ED) is aimed at detecting event occurrences and categorizing them. This task has been previously solved via recognition and classification of event triggers (ETs), which are defined as the phrase or word most clearly expressing event occurrence. Thus, current approaches require both annotated triggers as well as event types in training data. Nevertheless, triggers are non-essential in ED, and it is time-wasting for annotators to identify the “most clearly” word from a sentence, particularly in longer sentences. To decrease manual effort, we evaluate event detection without triggers. We propose a novel framework that combines Type-aware Attention and Graph… More >

Zubair Nabi¹, Ramzan Talib^1,*, Muhammad Kashif Hanif¹, Muhammad Awais²

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1357-1374, 2022, DOI:10.32604/csse.2022.025712

Abstract Digitalization has changed the way of information processing, and new techniques of legal data processing are evolving. Text mining helps to analyze and search different court cases available in the form of digital text documents to extract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reduced time. The rapid development of judicial ontologies seems to deliver interesting problem solving to legal knowledge formalization. Mining context information through ontologies from corpora is a challenging and interesting field. This research paper presents a three tier contextual text… More >

Sheng Huang, Chuanle Liu^*

Journal on Artificial Intelligence, Vol.3, No.4, pp. 153-162, 2021, DOI:10.32604/jai.2021.025175

Abstract Knowledge graph technology play a more and more important role in various fields of industry and academia. This paper firstly introduces the general framework of the knowledge graph construction, which includes three stages: information extraction, knowledge fusion and knowledge processing. In order to improve the efficiency of quality and safety supervision of transportation engineering construction, this paper constructs a knowledge graph by acquiring multi-sources heterogeneous data from supervision of transportation engineering quality and safety. It employs a bottom-up construction strategy and some natural language processing methods to solve the problems of the knowledge extraction for transportation engineering construction. We use… More >

Sunil Kumar¹, Hanumat G. Sastry¹, Venkatadri Marriboyina², Hammam Alshazly^3,*, Sahar Ahmed Idris⁴, Madhushi Verma⁵, Manjit Kaur⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5021-5038, 2022, DOI:10.32604/cmc.2022.021149

Abstract Information extraction plays a vital role in natural language processing, to extract named entities and events from unstructured data. Due to the exponential data growth in the agricultural sector, extracting significant information has become a challenging task. Though existing deep learning-based techniques have been applied in smart agriculture for crop cultivation, crop disease detection, weed removal, and yield production, still it is difficult to find the semantics between extracted information due to unswerving effects of weather, soil, pest, and fertilizer data. This paper consists of two parts. An initial phase, which proposes a data preprocessing technique for removal of ambiguity… More >

Kumari Sheeja Saraswathy, Sobha Lalitha Devi^*

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1983-1999, 2021, DOI:10.32604/cmc.2021.015661

Abstract The sentiment of a text depends on the clausal structure of the sentence and the connectives’ discourse arguments. In this work, the clause boundary, discourse argument, and syntactic and semantic information of the sentence are used to assign the text’s sentiment. The clause boundaries identify the span of the text, and the discourse connectives identify the arguments. Since the lexicon-based analysis of traditional sentiment analysis gives the wrong sentiment of the sentence, a deeper-level semantic analysis is required for the correct analysis of sentiments. Hence, in this study, explicit connectives in Malayalam are considered to identify the discourse arguments. A… More >

Yeon-Sun Ahn, Ok-Ran Jeong^*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2695-2708, 2021, DOI:10.32604/cmc.2021.015636

Abstract A knowledge graph is a structured graph in which data obtained from multiple sources are standardized to acquire and integrate human knowledge. Research is being actively conducted to cover a wide variety of knowledge, as it can be applied to applications that help humans. However, existing researches are constructing knowledge graphs without the time information that knowledge implies. Knowledge stored without time information becomes outdated over time, and in the future, the possibility of knowledge being false or meaningful changes is excluded. As a result, they can’t reflect information that changes dynamically, and they can’t accept information that has newly… More >

Varghese S. Chooralil¹, Vinodh P. Vijayan², Biju Paul¹, M. M. Anishin Raj³, B. Karthikeyan^4,*, G. Manikandan⁴

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2891-2903, 2021, DOI:10.32604/cmc.2021.012796

Abstract Key information extraction can reduce the dimensional effects while evaluating the correct preferences of users during semantic data analysis. Currently, the classifiers are used to maximize the performance of web-page recommendation in terms of precision and satisfaction. The recent method disambiguates contextual sentiment using conceptual prediction with robustness, however the conceptual prediction method is not able to yield the optimal solution. Context-dependent terms are primarily evaluated by constructing linear space of context features, presuming that if the terms come together in certain consumer-related reviews, they are semantically reliant. Moreover, the more frequently they coexist, the greater the semantic dependency is.… More >

Zhibin Zhang^1,2,*, Ping Li^1,3, Shuailing Zhao^1,2, Zhimin Lv^1,2, Fang Du^1,2, Yajian An^1,2

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1043-1056, 2021, DOI:10.32604/cmc.2020.012517

Abstract As the agricultural internet of things (IoT) technology has evolved, smart agricultural robots needs to have both flexibility and adaptability when moving in complex field environments. In this paper, we propose the concept of a vision-based navigation system for the agricultural IoT and a binocular vision navigation algorithm for smart agricultural robots, which can fuse the edge contour and the height information of rows of crop in images to extract the navigation parameters. First, the speeded-up robust feature (SURF) extracting and matching algorithm is used to obtain featuring point pairs from the green crop row images observed by the binocular… More >

Tahani Almutairi^1,*, Maha Al-yahya²

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 741-751, 2019, DOI:10.32604/cmc.2019.06239

Abstract Text visualization is concerned with the representation of text in a graphical form to facilitate comprehension of large textual data. Its aim is to improve the ability to understand and utilize the wealth of text-based information available. An essential task in any scientific research is the study and review of previous works in the specified domain, a process that is referred to as the literature survey process. This process involves the identification of prior work and evaluating its relevance to the research question. With the enormous number of published studies available online in digital form, this becomes a cumbersome task… More >