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Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format Example of Information and Computation format
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This content is only for preview purposes. The original open access content can be found here.
open access Open Access

Information and Computation — Template for authors

Publisher: Elsevier
Categories Rank Trend in last 3 yrs
Computational Theory and Mathematics #57 of 133 down down by 7 ranks
Computer Science Applications #328 of 693 down down by 57 ranks
Information Systems #164 of 329 down down by 30 ranks
Theoretical Computer Science #63 of 120 down down by 9 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 325 Published Papers | 866 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 13/06/2020
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Related Journals

open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 13.3
SJR: 1.36
SNIP: 4.097
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Springer

Quality:  
Good
CiteRatio: 3.8
SJR: 0.373
SNIP: 0.98
open access Open Access

Elsevier

Quality:  
Medium
CiteRatio: 2.3
SJR: 0.415
SNIP: 0.836
open access Open Access
recommended Recommended

Taylor and Francis

Quality:  
High
CiteRatio: 6.8
SJR: 1.321
SNIP: 1.764

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

0.872

5% from 2018

Impact factor for Information and Computation from 2016 - 2019
Year Value
2019 0.872
2018 0.83
2017 1.077
2016 1.05
graph view Graph view
table view Table view

2.7

CiteRatio for Information and Computation from 2016 - 2020
Year Value
2020 2.7
2019 2.7
2018 2.6
2017 2.2
2016 2.6
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has increased by 5% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.514

10% from 2019

SJR for Information and Computation from 2016 - 2020
Year Value
2020 0.514
2019 0.573
2018 0.584
2017 0.504
2016 0.724
graph view Graph view
table view Table view

1.116

7% from 2019

SNIP for Information and Computation from 2016 - 2020
Year Value
2020 1.116
2019 1.203
2018 1.16
2017 1.2
2016 1.248
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 10% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 7% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Information and Computation

Guideline source: View

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Use of these names, trademarks and brands does not imply endorsement or affiliation. Disclaimer Notice

Elsevier

Information and Computation

Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in a...... Read More

Mathematics

i
Last updated on
13 Jun 2020
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ISSN
0890-5401
i
Impact Factor
High - 1.584
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
i
Bibliography Name
elsarticle-num
i
Citation Type
Numbered
[25]
i
Bibliography Example
G. E. Blonder, M. Tinkham, T. M. Klapwijk, Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion, Phys. Rev. B 25 (7) (1982) 4515–4532. URL 10.1103/PhysRevB.25.4515

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1016/S0019-9958(62)90649-6
Programs for machine learning Part I
Aiko M. Hormann1

Abstract:

This paper reports on a proposed schema and gives some detailed specifications for constructing a learning system by means of programming a computer. We have tried to separate learning processes and problem-solving techniques from specific problem content in order to achieve generality, i.e., in order to achieve a system capa... This paper reports on a proposed schema and gives some detailed specifications for constructing a learning system by means of programming a computer. We have tried to separate learning processes and problem-solving techniques from specific problem content in order to achieve generality, i.e., in order to achieve a system capable of performing in a wide variety of learning and problem-solving situations. Behavior of the system is determined by both a direct and an indirect means. The former involves detailed, explicit specification of responses or response patterns in the form of built-in programs. The indirect means is by programs representing three mechanisms: a “community unit” (a program-providing mechanism), a planning mechanism, and an induction mechanism. These mechanisms have in common the following features: (1) a directly given repertory of response patterns; (2) general and less explicitly specified decision making rules and hierarchically distributed authority for decision making; (3) an ability to delegate some control over the system's behavior to the environment; and (4) a self-modifying ability which allows the decision-making rules and the repertory of response patterns to adapt and grow. In Part I of this paper, the community unit is described and an illustration of its operation is given. It is presented in a schematized framework as a team of routines connected by first and second-order feedback loops. The function of the community unit is to provide higher-level programs (its environment or customers) with programs capable of performing requested tasks, or to perform a customer-stipulated task by executing a program. If the community unit does not have a ready-made program in stock to fill a particular request, internal programming will be performed, i.e., the community unit will have to construct a program, and debug it, before outputting or executing it. The primary purpose of internal programming is to assist higher-level programs in performing tasks for which detailed preplanning by an external programmer is either impossible or impractical. Some heuristics are suggested for enabling the community unit to search for a usable sequence of operations more efficiently than if it were to search simply by exhaustive or random trial and error. These heuristics are of a step-by-step nature. For complex problems, however, such step-by-step heuristics alone will fail unless there is also a mechanism for analyzing problem structure and placing guideposts on the road to the goal. A planning mechanism capable of doing this is proposed in Part II. Under the control of a higher-level program which specifies the level of detail required in a plan being developed, this planning mechanism is to break up problems into a hierarchy of subproblems each by itself presumably easier to solve than the original problem. To manage classes of problems and to make efficient use of past experience, an induction mechanism is proposed in Part II. An illustration is given of the induction mechanism solving a specific sequence of tasks. The system is currently being programmed and tested in IPL-V on the Philco 2000 computer. The current stage of the programming effort is reported in an epilogue to Part II. read more read less

Topics:

Heuristics (56%)56% related to the paper, Trial and error (50%)50% related to the paper
3,719 Citations
open accessOpen access Journal Article DOI: 10.1016/S0019-9958(67)91165-5
Language identification in the limit

Abstract:

Language learnability has been investigated. This refers to the following situation: A class of possible languages is specified, together with a method of presenting information to the learner about an unknown language, which is to be chosen from the class. The question is now asked, “Is the information sufficient to determin... Language learnability has been investigated. This refers to the following situation: A class of possible languages is specified, together with a method of presenting information to the learner about an unknown language, which is to be chosen from the class. The question is now asked, “Is the information sufficient to determine which of the possible languages is the unknown language?” Many definitions of learnability are possible, but only the following is considered here: Time is quantized and has a finite starting time. At each time the learner receives a unit of information and is to make a guess as to the identity of the unknown language on the basis of the information received so far. This process continues forever. The class of languages will be considered learnable with respect to the specified method of information presentation if there is an algorithm that the learner can use to make his guesses, the algorithm having the following property: Given any language of the class, there is some finite time after which the guesses will all be the same and they will be correct. In this preliminary investigation, a language is taken to be a set of strings on some finite alphabet. The alphabet is the same for all languages of the class. Several variations of each of the following two basic methods of information presentation are investigated: A text for a language generates the strings of the language in any order such that every string of the language occurs at least once. An informant for a language tells whether a string is in the language, and chooses the strings in some order such that every string occurs at least once. It was found that the class of context-sensitive languages is learnable from an informant, but that not even the class of regular languages is learnable from a text. read more read less

Topics:

Language identification in the limit (71%)71% related to the paper, Context-free language (63%)63% related to the paper, Language primitive (62%)62% related to the paper, Natural language (62%)62% related to the paper, Picture language (62%)62% related to the paper
3,460 Citations
open accessOpen access Journal Article DOI: 10.1016/0890-5401(92)90008-4
A calculus of mobile processes, II
Robin Milner1, Joachim Parrow2, David Walker3

Abstract:

We present the a-calculus, a calculus of communicating systems in which one can naturally express processes which have changing structure. Not only may the component agents of a system be arbitrarily linked, but a communication between neighbours may carry information which changes that linkage. The calculus is an extension o... We present the a-calculus, a calculus of communicating systems in which one can naturally express processes which have changing structure. Not only may the component agents of a system be arbitrarily linked, but a communication between neighbours may carry information which changes that linkage. The calculus is an extension of the process algebra CCS, following work by Engberg and Nielsen, who added mobility to CCS while preserving its algebraic properties. The rr-calculus gains simplicity by removing all distinction between variables and constants; communication links are identified by names, and computation is represented purely as the communication of names across links. After an illustrated description of how the n-calculus generalises conventional process algebras in treating mobility, several examples exploiting mobility are given in some detail. The important examples are the encoding into the n-calculus of higher-order functions (the I-calculus and combinatory algebra), the transmission of processes as values, and the representation of data structures as processes. The paper continues by presenting the algebraic theory of strong bisimilarity and strong equivalence, including a new notion of equivalence indexed by distinctions-i.e., assumptions of inequality among names. These theories are based upon a semantics in terms of a labeled transition system and a notion of strong bisimulation, both of which are expounded in detail in a companion paper. We also report briefly on work-in-progress based upon the corresponding notion of weak bisimulation, in which internal actions cannot be observed. 0 1992 Academic Press, Inc. read more read less

Topics:

Process calculus (61%)61% related to the paper, Calculus of communicating systems (59%)59% related to the paper, Pattern calculus (56%)56% related to the paper, Ambient calculus (56%)56% related to the paper, Bisimulation (56%)56% related to the paper
3,093 Citations
open accessOpen access Journal Article DOI: 10.1016/0890-5401(87)90052-6
Learning regular sets from queries and counterexamples
Dana Angluin1

Abstract:

The problem of identifying an unknown regular set from examples of its members and nonmembers is addressed. It is assumed that the regular set is presented by a minimaMy adequate Teacher, which can answer membership queries about the set and can also test a conjecture and indicate whether it is equal to the unknown set and pr... The problem of identifying an unknown regular set from examples of its members and nonmembers is addressed. It is assumed that the regular set is presented by a minimaMy adequate Teacher, which can answer membership queries about the set and can also test a conjecture and indicate whether it is equal to the unknown set and provide a counterexample if not. (A counterexample is a string in the symmetric difference of the correct set and the conjectured set.) A learning algorithm L* is described that correctly learns any regular set from any minimally adequate Teacher in time polynomial in the number of states of the minimum dfa for the set and the maximum length of any counterexample provided by the Teacher. It is shown that in a stochastic setting the ability of the Teacher to test conjectures may be replaced by a random sampling oracle, EX( ). A polynomial-time learning algorithm is shown for a particular problem of context-free language identification. read more read less

Topics:

Infinite set (62%)62% related to the paper, Counterexample (62%)62% related to the paper, Index set (62%)62% related to the paper, Set function (62%)62% related to the paper, Set (abstract data type) (57%)57% related to the paper
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2,157 Citations
open accessOpen access Journal Article DOI: 10.1006/INCO.1994.1009
The weighted majority algorithm
Nick Littlestone1, Manfred K. Warmuth1

Abstract:

We study the construction of prediction algorithms in a situation in which a learner faces a sequence of trials, with a prediction to be made in each, and the goal of the learner is to make few mistakes. We are interested in the case where the learner has reason to believe that one of some pool of known algorithms will perfor... We study the construction of prediction algorithms in a situation in which a learner faces a sequence of trials, with a prediction to be made in each, and the goal of the learner is to make few mistakes. We are interested in the case where the learner has reason to believe that one of some pool of known algorithms will perform well, but the learner does not know which one. A simple and effective method, based on weighted voting, is introduced for constructing a compound algorithm in such a circumstance. We call this method the Weighted Majority Algorithm. We show that this algorithm is robust in the presence of errors in the data. We discuss various versions of the Weighted Majority Algorithm and prove mistake bounds for them that are closely related to the mistake bounds of the best algorithms of the pool. For example, given a sequence of trials, if there is an algorithm in the pool A that makes at most m mistakes then the Weighted Majority Algorithm will make at most c(log |A| + m) mistakes on that sequence, where c is fixed constant. read more read less

Topics:

Weighted Majority Algorithm (76%)76% related to the paper, Randomized weighted majority algorithm (73%)73% related to the paper, Winnow (54%)54% related to the paper, Weighted voting (53%)53% related to the paper
2,093 Citations
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SciSpace is a very innovative solution to the formatting problem and existing providers, such as Mendeley or Word did not really evolve in recent years.

- Andreas Frutiger, Researcher, ETH Zurich, Institute for Biomedical Engineering

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With SciSpace, you do not need a word template for Information and Computation.

It automatically formats your research paper to Elsevier formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

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Time taken to format a paper and Compliance with guidelines

Plagiarism Reports via Turnitin

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Using this service, researchers can compare submissions against more than 170 million scholarly articles, a database of 70+ billion current and archived web pages. How Turnitin Integration works?

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Information and Computation format uses elsarticle-num citation style.

Automatically format and order your citations and bibliography in a click.

SciSpace allows imports from all reference managers like Mendeley, Zotero, Endnote, Google Scholar etc.

Frequently asked questions

1. Can I write Information and Computation in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Information and Computation guidelines and auto format it.

2. Do you follow the Information and Computation guidelines?

Yes, the template is compliant with the Information and Computation guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Information and Computation?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Information and Computation citation style.

4. Can I use the Information and Computation templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Information and Computation.

5. Can I use a manuscript in Information and Computation that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Information and Computation that you can download at the end.

6. How long does it usually take you to format my papers in Information and Computation?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Information and Computation.

7. Where can I find the template for the Information and Computation?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Information and Computation's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Information and Computation's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Information and Computation an online tool or is there a desktop version?

SciSpace's Information and Computation is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Information and Computation?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Information and Computation?”

11. What is the output that I would get after using Information and Computation?

After writing your paper autoformatting in Information and Computation, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Information and Computation's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Information and Computation?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Information and Computation. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Information and Computation?

The 5 most common citation types in order of usage for Information and Computation are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Information and Computation?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Information and Computation's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Information and Computation in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Information and Computation Endnote style according to Elsevier guidelines.

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Typset automatically formats your research paper to Information and Computation formatting guidelines and citation style.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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