To decide that a work is suitable for a conference or a in the field of Computer Science & Engineering . You have to see thoroughly the quality and quantity of data available. Journal demands novelty of data which is refereed further. The sustainability is very important for publications in journals

1. Both the scope of the journal and your work matches

2. Select high Impact factor journal on the computer science stream.

3. Check similar nature of work is available in that journal.

Dear Susovan Jana

The following link is useful.

https://homes.cs.washington.edu/~mernst/advice/conferences-vs-journals.html

Regards.

You need to read in details what is the conference about and what is the aim of holding that conference.

I would say it is about the novelty of your work, and substantiation of your claims.

Firstly, many conferences nowadays can be more prestigious than journals and more competitive especially in computer science. In other fields, the hiring mangers would only consider journal publications and think conference does not worth counting as a publication. My recommendation, is to compare your work against published papers in terms of quality, novelty and contribution. Another difference is that for journals you have time to review and change before getting accepted, but this is not the case for conferences. The time frame is also different, conferences are faster to publish than journals. In my field of computer vision and machine learning, we usually make a conference paper to get feedback of wider audience about new ideas and use their feedback to polish the work and add more experiments and analysis to submit to a quality journal. Hope this help.

The decision is based on the maturity level of ongoing research. Suppose one start a research project as a PhD student, so the first findings of the research may be suitable for submission in conference. In the next phase of more training, such ongoing research may definitely be more mature, with more contribution, more experiments and more explanation.,....more experience in writing,. Etc.,. so the manuscript at this stage may be more suitable for some relevant journal.

The synthesis of the semantic nuclei of scientific specialties of the higher attestation commission of the Russian Federation and the automatic classification of articles according to scientific fields with the use of ASC-analysis and "Eidos" intellectual systems. 14 January 2019 at the website of the higher attestation Commission of the Russian Federation http://vak.ed.gov.ru/87 the information appeared: "About refining of scientific specialties and their respective fields of science where publications are included in the List of peer-reviewed scientific publications, where basic scientific results of dissertations on competition of a scientific degree of candidate of Sciences, on competition of a scientific degree of the doctor of Sciences must be published ". It is reported that according to the recommendation of the HAC for other publications included in the List of groups of scientific specialties, the work on refining scientific specialties and branches of science will be continued in 2019. This work is a continuation of the author's series of works on cognitive linguistics. It offers innovative intelligent technology to automate the solution of the problem formulated by the higher attestation Commission of the Russian Federation above. With the use of the automated system-cognitive analysis (ASC-analysis) and its programmatic toolkit which is intellectual system called "Eidos" directly on the basis of official texts of passports of scientific specialties of the higher attestation Commission of the Russian Federation, there were established their semantic kernels, and then, implemented the automatic classification of scientific texts (articles, monographs, textbooks, etc.) on the specialties and groups of specialties of the higher attestation Commission of the Russian Federation. Traditionally, this task is solved by dissertation councils, as well as editorial boards of scientific publications, i.e. by experts, on the basis of expert assessments, in an informal way, on the basis of experience, intuition and professional competence. However, the traditional approach has a number of serious drawbacks that impose significant limitations on the quality and volume of analysis. Therefore, the efforts of researchers and developers to overcome these limitations are relevant. Currently, there are all grounds to consider these restrictions as unacceptable, because they are not only necessary, but also quite possible to overcome. Thus, there is a problem, the solution of which is the subject of consideration in this article. A detailed numerical example of solving the problem on real data is given as well.

Article The synthesis of the semantic nuclei of scientific specialti...

Formation of a semantic kernel in veterinary medicine with the automated system-cognitive analysis of passports of scientific specialties of the higher attestation commission of the Russian federation and the automatic classification of texts according to the areas of science. This work is a continuation of the author's series of works on cognitive veterinary medicine. The present period is characterized by the appearance of huge volumes of texts in different languages in the open access, generated by people. Currently, these texts are accumulated in various electronic libraries and bibliographic databases (WoS, Scopus, RSCI, etc.), as well as on the Internet on various sites. All these texts have specific authors, dates and can belong simultaneously to many non-alternative categories and genres, in particular: educational; scientific; artistic; political; news; chats; forums and many others. The solution of the generalized problem of attribution of texts is of great scientific and practical interest, i.e. studying these texts, which would reveal their probable authors, date of creation, the ownership of these texts to the above generalized categories or genres, and might evaluate the similarities - differences of authors and texts according to their content, highlight key words etc. To solve all these problems it seems necessary to form the generalized linguistic images of texts into groups (classes), i.e. to form semantic kernels of classes. A special case of this problem is the creation of the semantic kernel in various scientific specialties of the HAC of the Russian Federation and the automatic classification of scientific texts in the areas of science. Traditionally, this task is solved by dissertation councils, i.e. experts, on the basis of expert assessments, i.e. in an informal way, on the basis of experience, intuition and professional competence. However, the traditional approach has a number of serious drawbacks that impose significant limitations on the quality and volume of analysis. Currently, there are all grounds to consider these restrictions as unacceptable, because they can be overcome. Thus, there is a problem, the solutions of which are the subject of consideration in this article. Therefore, the efforts of researchers and developers to overcome them are relevant. Therefore, the aim of the work is to develop an automated technology (method and tools), as well as methods of their application for the formation of the semantic core of veterinary medicine by automated system-cognitive analysis of passports of scientific specialties of the HAC of the Russian Federation and automatic classification of texts in the areas of science. A detailed numerical example of solving the problem on real data has been given as well.

Article FORMATION OF A SEMANTIC KERNEL IN VETERINARY MEDICINE WITH T...

http://lc.kubagro.ru/aidos/Works_on_ASK-analysis_of_texts.htm

Thank you all.