Computacion y Sistemas

Top Research Topics at Computación Y Sistemas?

Computación Y Sistemas generally zeroes in on subjects such as Artificial intelligence, Natural language processing, Humanities, Pattern recognition and Information retrieval. While it focused on Artificial intelligence, it was also able to explore topics like Machine learning and Computer vision.

• Artificial intelligence (14.24%)
• Natural language processing (7.46%)
• Humanities (3.62%)

What are the most cited papers published in the journal?

• Soft Similarity and Soft Cosine Measure: Similarity of Features in Vector Space Model (183 citations)
• Spotting fake reviews using positive-unlabeled learning (58 citations)
• Qué es la filosofía de la tecnología (29 citations)

Research areas of the most cited articles at Computación Y Sistemas:

The journal publications aim to foster the development of research in Artificial intelligence, Natural language processing, Information retrieval, Machine learning and Hindi. The published articles dive deep in exploring the relationship between the study of Artificial intelligence and Modern Standard Arabic. The journal publications explore issues in Natural language processing which can be linked to other research areas like Heuristics, Information overload and Compression (functional analysis).

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Statistics
• Law

The previous edition focused in particular on these issues:

The journal explores disciplines such as Artificial intelligence, Tourism, Natural language processing, Pattern recognition and Context (language use). Artificial intelligence study tackled is connected to the field of Machine learning. The studies on Tourism discussed can also contribute to research in the domains of Economic growth, Naturalistic observation, Participant observation, Psychological resilience and Work (electrical).

Topics in Natural language processing explored in the journal were investigated in conjunction with research in Regular expression, Recall, Order (exchange) and Data set. Aside from discussions in Context (language use), Computación Y Sistemas also deals with the subject of Open research which intersects with Field (computer science) disciplines. The journal focuses on Deep learning but the discussions also offer insight into other areas such as Sentiment analysis, Recurrent neural network, Contextual image classification and Sentence.

The most cited articles from the last journal are:

• Transformer-Based Extractive Social Media Question Answering on TweetQA (1 citations)
• Rule-Based Spanish Multiple Question Reformulation and their Classification using a Convolutional Neuronal Network (1 citations)
• Registro, documentación e interpretación del arte rupestre. Una propuesta básica para estudiantes: el Seminario Taller de la SIARB (0 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Computación Y Sistemas (based on the number of publications) are:

• Ciencia y Sociedad CyS (24 papers) absent at the last edition,
• Alexander Gelbukh (19 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• Rocío Hernández Mella (15 papers) absent at the last edition,
• César Cuello Nieto (15 papers) absent at the last edition,
• Eduardo Latorre (14 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Computación Y Sistemas (based on the number of publications) are:

• Instituto Tecnológico de Santo Domingo (750 papers) published 4 papers at the last edition the same number as at the previous edition,
• Instituto Politécnico Nacional (103 papers) published 7 papers at the last edition, 6 less than at the previous edition,
• Benemérita Universidad Autónoma de Puebla (40 papers) absent at the last edition,
• Universidad Autónoma de Santo Domingo (39 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• University of Cienfuegos (26 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 39.29% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 47.06% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.82% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 14.71% of all publications and 29.41% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Further Learning Opportunities for Interested Researchers in the Field

If you're interested in these topics and want to explore a career in teaching related subjects, you might be wondering where to start. Whether you are looking to gain further understanding or considering a career transition, there are resources to guide you. A specific path many consider is teaching; this offers the opportunity to directly impact the next generation of developers and pioneers in the field. For instance, a resource exists on how to transition into teaching in South Dakota specifically, which could be a great place for budding educators to start.

Learning the requirements and processes to become a teacher in South Dakota with a bachelor's degree could help you understand the necessary steps to take this career path. Teaching can be a fulfilling way to not only deepen your own understanding of these topics but also to cultivate a passion for them in others. If you're passionate about artificial intelligence, natural language processing, or any of the other topics that Computación Y Sistemas researches, teaching could be your way to give back and inspire others in the field.

As you explore these possibilities, remember the deep, varied universe these subjects contain, and consider how you could contribute to it through teaching. Understanding and teaching these subjects will allow you to engage with communities of scholars and teachers, shaped by different institutions and academic landscapes, all contributing to the advancement of artificial intelligence, natural language processing, and more.