Keyword extraction is essential in determining influenced keywords from huge documents as the research repositories are becoming massive in volume day by day. The research community is drowning in data and starving for information. The keywords are the words that describe the theme of the whole document in a precise way by consisting of just a few words. Furthermore, many state-of-the-art approaches are available for keyword extraction from a huge collection of documents and are classified into three types, the statistical approaches, machine learning, and graph-based methods. The machine learning approaches require a large training dataset that needs to be developed manually by domain experts, which sometimes is difficult to produce while determining influenced keywords. However, this research focused on enhancing state-of-the-art graph-based methods to extract keywords when the training dataset is unavailable. This research first converted the handcrafted dataset, collected from impact factor journals into n-grams combinations, ranging from unigram to pentagram and also enhanced traditional graph-based approaches. The experiment was conducted on a handcrafted dataset, and all methods were applied on it. Domain experts performed the user study to evaluate the results. The results were observed from every method and were evaluated with the user study using precision, recall and f-measure as evaluation matrices. The results showed that the proposed method (FNG-IE) performed well and scored near the machine learning approaches score.
The idea behind exertion to build up remote device organize framework to persistently screen and identify cardiovascular poison accomplished patients by the side of isolated regions. A remote sensor framework intended toward persistently catches and communicates the ECG signs to the patient's device. Internet of Things (IoT) is a conventional element of life by raising the communication and networking anytime, anyplace. Security requirements for IoT is most likely emphasize the importance of precisely start, operate, and forced security arrangement for the duration of their life-cycle. The key of the exploration is basically to concentrate on health related to sensors and monitors to keep track of critical signs by using smart clothes. The aim is to make a framework where diverse sorts of sensors is coordinate into textiles to be utilized as a part of constant checking by people utilizing adaptable and wearable frameworks. The consequences from the administer used to formulate analysis and to detect movement in order to sustain the people to keep away from heart threat reason and help to avoid heart attack and other discriminating actions. Micro sensors embedded all through the shirt that proficient to monitor data. The primary thought of this to discover the possibility of performing dependable respiratory administers by a method for garments raised area.
The research volume increases at the study rate, causing massive text corpora. Due to these enormous text corpora, we are drowning in data and starving for information. Therefore, recent research employed different text mining approaches to extract information from this text corpus. These proposed approaches extract meaningful and precise phrases that effectively describe the text's information. These extracted phrases are commonly termed keyphrases. Further, these key phrases are employed to determine the different fields of study trends. Moreover, these key phrases can also be used to determine the spatiotemporal trends in the various research fields. In this research, the progress of a research field can be better revealed through spatiotemporal bibliographic trend analysis. Therefore, an effective spatiotemporal trend extraction mechanism is required to disclose textile research trends of particular regions during a specific period. This study collected a diversified dataset of textile research from 2011-2019 and different countries to determine the research trend. This data was collected from various open access journals. Further, this research determined the spatiotemporal trends using quality phrase mining. This research also focused on finding the research collaboration of different countries in a particular research subject. The research collaborations of other countries' researchers show the impact on import and export of those countries. The visualization approach is also incorporated to understand the results better.
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