Topic Space Research Articles

Automatic Extractive and Generic Document Summarization Based on NMF

Abstract Nowadays, textual information grows exponentially on the Internet. Text summarization (TS) plays a crucial role in the massive amount of textual content. Manual TS is time-consuming and impractical in some applications with a huge amount of textual information. Automatic text summarization (ATS) is an essential technology to overcome mentioned challenges. Non-negative matrix factorization (NMF) is a useful tool for extracting semantic contents from textual data. Existing NMF approaches only focus on how factorized matrices should be modeled, and neglect the relationships among sentences. These relationships provide better factorization for TS. This paper suggests a novel non-negative matrix factorization for text summarization (NMFTS). The proposed ATS model puts regularizes on pairwise sentences vectors. A new cost function based on the Frobenius norm is designed, and an algorithm is developed to minimize this function by proposing iterative updating rules. The proposed NMFTS extracts semantic content by reducing the size of documents and mapping the same sentences closely together in the latent topic space. Compared with the basic NMF, the convergence time of the proposed method does not grow. The convergence proof of the NMFTS and empirical results on the benchmark data sets show that the suggested updating rules converge fast and achieve superior results compared to other methods.

Energetic Competencies in Electronic Engineering Education: A Sustainable Social Commitment

Abstract: In this article, we present electronic engineering as a discipline called to propose solutions to achieve energy sustainability. This field of knowledge has been supported to accelerate energy consumption with technological contributions to al low the comfort s of the modern world. Consequently, electronics has influenced advances such as transport systems, innovations in means of communication, automation of production, domotics, and all direct impacts in the economic, political, and educational sectors. In the same way, it is then possible for electronic technology to promote development both in generating energy resources in a sustainable way and by reducing micro and macro consumption. Up to now, engineering education has promoted scientific and technological training to provide solutions that address the different needs of society, including alternative energy transformation systems. However, it has not been concerned with including in each lesson an awareness of energy efficiency and developing solutions based on sustainable use of energy. Up to now, engineering education has promoted scientific and technologicaltraining to provide solutions that address the different needs of society, including alternative energy transformation systems. Nevertheless, it has not been concerned with including in each lesson an awareness of energy efficiency and developing solutions based on sustainable use of energy. As a resource of help, we propose in this work the inclusion of "energy competences" in each topic and learning space from an Electronic Engineering program. The work presented shows that it is possible to include energy competences in electronic engineering curricula as a part of an educational sustainable social commitment. Keywords: Learning spaces, sustainability, energy, engineering education, energy competencies, syllabus.

Topic-word-constrained sentence generation with variational autoencoder

• A model that can generate sentences under topic and word constraints was proposed. • It uses multiple Gaussian distributions as the prior for the latent code in the VAE. • It has an expanded semantically meaningful and smooth latent space for sentences. • It gets rid of the KL collapse problem in the VAE. • It uses the topic and sentence latent codes to guide generation together. We propose a topic-word-constrained sentence-generation model with a variational autoencoder and convolutional neural network . It can generate sentences conditioned on a given topic distribution and a certain word. Unlike the vanilla variational autoencoder that assumes a standard Gaussian prior for the latent code, our model specifies the prior for the topic latent code as multiple Gaussian distributions, where each Gaussian distribution corresponds to a topic vector parameterized by a convolutional neural topic model. For word constraints, the decoder in the variational autoencoder generates sentences backward and forward starting from a given word. The topic latent space is arranged by the similarity of topic vectors, and the topic latent code restricts the sentence latent code through a loss term, through which expanded semantically meaningful latent spaces can be learned and provide topic guidance while generating sentences. Experimental results show that our model can generate coherent and diverse sentences related to given topics and words, while also avoiding the Kullback–Leibler divergence collapse problem. Moreover, it outperforms alternative approaches in terms of sentence reconstruction, latent space property and the quality, diversity, and topic controllability of generated sentences.

FORKING PATHS OF CULTURAL COMPLEXITY: A CASE STUDY OF RESEARCH PARADIGMS

Evolutionary studies of cultural complexity often assume that group members select the best information available in the group, effectively diffusing the best innovations, whose advantages are subsequently passed on to the next generation. This would seem to describe the ideal of the scientific process — each cohort of papers in a field surfacing the best innovations, refining them and passing on to the next “layer” or cohort of scientific works. Here, we use academic journal databases to explore this “forking” (branching) process in the evolution of a scientific paradigm. We apply citation network visualization and Latent Dirichlet allocation topic analysis to three different paradigms defined pragmatically as the set of papers citing a highly influential paper in each respective case. Our three case studies indicate a founder effect in how the seminal paper is highly-embedded in the citation network, and yet peripheral to the evolution of topics in subsequent “layers” of publications within the paradigm. This and additional evidence suggest certain topics are selected and followed, while others are left behind. From these case studies, we discuss how hitherto undeveloped ideas of the past might be located in the topic space of seminal works of the same fruitful time period.

Filozofia spomienok. K filozofickej a literánej metodológii Straussovho diela Človek pre nikoho

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

The Memory of Saints Cyril and Methodius in Thessaloniki

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

The Seals of Medieval Hungarian Kingdom as Means of Communication in Court Practice and Property Protection

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Calendar for the Greek Catholic Slovaks for the year 1941

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Orthodoxy as an Important Element of Modern Greek Identity in the 1860s – 1910s (An Example of the Greek Church of St. Nicholas in Batum)

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Počiatky proanjouovského postoja Rádu svätého Jána Jeruzalemského v Uhorsku vo svetle johanitskej komunikácie

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Sv. František a hledání „nového“ křesťanství v ruské filozofii první poloviny 20. století (D. Merežkovskij a N. Berďajev)

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Cyrilometodějská tradice v pojetí české společnosti 21. století

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Kultúrno-historický rozmer cyrilo-metodskej misie v kontexte neskorších cirkevných diel na Slovensku (Rituale Strigoniense, Rituale Slovacchiæ a Cantus catholici)

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

The Icon of the Virgin and the Child with Archangels, and Saints. Work of the Artist-Priest Emmanuel Tzanes (1668) From the Sacristy of the Monastery of Varlaam/Meteora-Thessaly

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Українське євангеліє 17 cт. у Бібліотеці честера бітті: історія створення, користування та переміщення

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Monastic Identity of Constantine the Philosopher and Methodius and the First Slavic Translations of Ascetic Texts

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

Ethnos and Ethos: Slovak Slavic Reciprocity and Greek Cypriot Enosis

Konštantínove listy/Constantine’s Letters is an international scientific journal which has been published in Constantine the Philosopher University in Nitra since 2008. The main goal of the journal is to present problems and themes intertwined with the cultural and political history of Great Moravia during the 9th century as well as continuity of Cyrillo-Methodian tradition in later times. Next, there is also space for other adjacent topics connected with Slavonic and Byzantine history, philology, philosophy, literature, cultural relations as well as medieval and early modern age ecclesiastical history and iconography.

A context-enhanced sentence representation learning method for close domains with topic modeling

Sentence representation approaches have been widely used and proven to be effective in many text modeling tasks and downstream applications. Many recent proposals are available on learning sentence representations based on deep neural frameworks. However, these methods are pre-trained in open domains and depend on the availability of large-scale data for model fitting. As a result, they may fail in some special scenarios, where data are sparse and embedding interpretations are required, such as legal, medical, or technical fields. In this paper, we present an unsupervised learning method to exploit representations of sentences for some closed domains via topic modeling. We reformulate the inference process of the sentences with the corresponding contextual sentences and the associated words, and propose an effective context-enhanced process called the bi-Directional Context-enhanced Sentence Representation Learning (bi-DCSR). This method takes advantage of the semantic distributions of the nearby contextual sentences and the associated words to form a context-enhanced sentence representation. To support the bi-DCSR, we develop a novel Bayesian topic model to embed sentences and words into the same latent interpretable topic space called the Hybrid Priors Topic Model (HPTM). Based on the defined topic space by the HPTM, the bi-DCSR method learns the embedding of a sentence by the two-directional contextual sentences and the words in it, which allows us to efficiently learn high-quality sentence representations in such closed domains. In addition to an open-domain dataset from Wikipedia, our method is validated using three closed-domain datasets from legal cases, electronic medical records, and technical reports. Our experiments indicate that the HPTM significantly outperforms on language modeling and topic coherence, compared with the existing topic models. Meanwhile, the bi-DCSR method does not only outperform the state-of-the-art unsupervised learning methods on closed domain sentence classification tasks, but also yields competitive performance compared to these established approaches on the open domain. Additionally, the visualizations of the semantics of sentences and words demonstrate the interpretable capacity of our model.

A scientific research topic trend prediction model based on multi‐LSTM and graph convolutional network

Predicting the development trend of future scientific research not only provides a reference for researchers to understand the development of the discipline, but also provides support for decision-making and fund allocation for decision-makers. The continuous growth of scientific publications has brought challenges to track the development trends of scientific research topics. The existing topic trend prediction methods have proved that the research topic trend of a publication is influenced by other peer publications. However, they ignore the fact that the research topics of different publications belong to different research topic space. Moreover, the existing topic prediction methods do not fully consider the interactive influence among publications that the research topic of one publication affects the topics of other publications, it is also influenced by the research topics of other publications. In line with this, this paper proposes a scientific research topic trend prediction model based on multi-long short-term memory (multi-LSTM) and Graph Convolutional Network. Specifically, multiple LSTMs are employed to map research topics of different publications into their respective topic space. Then, the graph convolutional neural network is applied to learn the scientific influence context of each publication, so that the research topic of each publication not only integrates the influence of neighbor nodes, but also considers the influence of the neighbors of the neighbor node on the research topic of the publication, so as to more accurately fuse scientific influence context of research topic of peer publications. Experiments results on the data set of scientific research papers in the field of artificial intelligence and data mining demonstrate that the model improves the prediction precision and achieves the state-of-the-art research topic trend prediction effect compared with the other baseline models.

An Analysis Model of Potential Topics in English Essays Based on Semantic Space

<p>With the reform of English examination in China in recent years, the automatic evaluation of English essays as subjective questions has always been the focus and difficulty of research. The existing automatic essay evaluation system (AEE) has obtained good feedback on the vocabulary, syntactic and other features of English essays, but there is still a problem of low accuracy in the analysis of potential topic in English essay. In order to solve this problem, this paper takes relational triples as the carrier to analyze the potential topics of English essays. By constructing the hierarchical topic trees hybrid semantic spaces to carry out topic clustering, distributed representation of topic relational triples and topic set extension in English essays. Then, based on the improved on-topic analysis algorithm in this paper, the paper analyzes the topic of English essay in multiple dimensions to obtain more abundant potential on-topic semantic information. The experiment results show that the proposed model can reduce the noise caused by non-topic words effectively, and improve the fine-grained topic semantic space in English essays, and the proposed model has better performance than the current methods of on-topic analysis in English esssays.</p> <p> </p>