Optimel: Software for selecting the optimal method

Popova, Olga; Popov, Boris; Romanov, Dmitry; Evseeva, Marina

doi:10.1016/j.softx.2017.08.001

Cited by 10 publications

(4 citation statements)

References 7 publications

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“…The measurement unit of D asi will be: (bit/bit)*1=1. As the standard for assessment of absolute dynamic value D si , the algorithm of structuring the domain knowledge suggested by the authors (Popova, Popov, Romanov & Evseeva, 2017) will be used.…”

Section: Obtaining the Absolute And The Relative Dynamic Measure Of S...mentioning

confidence: 99%

“…Authors in their previous works were able to obtain for the first time a model of an existing search research that does not use the knowledge structuring algorithm (Popova, Popov, Romanov & Evseeva, 2017). Such a model is necessary to obtain calculated data that help not only prove the effectiveness of the information structuring algorithm obtained earlier by the authors (Popova, Popov, Karandey & Gerashchenko, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Obtaining the Dynamic Coefficients of Structuredness for Assessing a Domain

Popova

Popov

Karandey

et al. 2022

International Journal of Cognitive Informatics and Natural Intelligence

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Today, effective management of information requires an in-depth study of its internal organization. The structural organization of information affects the efficiency of choosing a method for solving the problem and the qualitative presentation of information about the subject area. Therefore, the article proposes a new semiotic structural approach to assessing the structuredness of information in a subject area, as well as theoretical, practical, and general logical methods for studying the process of search research as a single system. The authors proposed and investigated the structured information coeffi-cient, which the authors propose to consider in several aspects - with respect to the search research model presented by the traditional algorithm, and the structured subject area. The article presents theo-retical positions, derives the formula of coefficients for different cases, carries out calculations on the example of the subject area “optimization methods”, constructs graphs based on the calculated data, and draws conclusions.

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Section: Obtaining the Absolute And The Relative Dynamic Measure Of S...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Obtaining the Dynamic Coefficients of Structuredness for Assessing a Domain

Popova

Popov

Karandey

et al. 2022

International Journal of Cognitive Informatics and Natural Intelligence

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“…Decisiontreesmakeitpossiblenotonlytoclassifyallobjectsbutalsotoobtainthetreestructure withtheoptimalcode (Abellán,Baker,Coolen,Crossman&Masegosa,2014;Pei,Hu&Chen,2016) havingtheminimallength.Thedemandforitgrowswiththeincreaseinthenumberofclassified objects, because the height of the tree increases as well. Here the resulting code is represented accordingtotheHuffmantreetype,bymeansofzerosandones.Forobtainingtheoptimaltreethey usetheinformationtheorymethodsuggestingtheusageofthenotionsofinformationgain (Ferreira &Vasilyev,2015;Abellán,2013)andentropy (Nurpratami&Sitanggang,2015;Kim,2016).The obtainedShannon'sformulaforthenodesofclassificationtreesandthebasicdefinitionstakenfrom informationtheoryprovideaconventionalwayofbuildingadecisiontree.Thewayofchoosingthe attribute (Kamadi,Allam,Thummala&Rao,2016;Ma,Destercke&Wang,2016)andtherulesfor obtainingthenodes (Ferreira&Vasilyev,2015;Abellán,López&deOña,2013)isalwaysacreative process,whichhasthepeculiaritiesconventionalforthistheory.Duetothefactthatclassificationtrees suggestaddingtheobjectsintheprocessofgettingnewexperience,theproblemofreconfiguringthe treeisactualhere.Soitisnecessarytodevelopthewaysofteachingthedecisionsupportsystemsusing suchtrees (Subburayalu,Jenhani&Slater,2014;Cui,Shi&Wang,2016).Theresultingsituationis asfollows.Therearenovolumelimitsfordescribingtheobjects,theirproperties,facts,etc.,which aretobeclassifiedandusedforsolvingthecomplexscientificandappliedtasksduetothemodern advancesincomputertechnology.Thelimitsstarttoappearwhentheapparatusofanalysisforthese facts,objects,etc.,isbeingarranged.Theselimitsarethedisadvantagesofusingthedecisiontree method,andtheyhavetobeurgentlycorrected.Theauthorssuggestanotherwaytoeliminatethe disadvantagesofthismethod:theyproposetochangetheconventionalapproachestousingit.The pre-existingapproachtousingthedecisiontreemethoddidnotmakeitpossibletosolveanumber oftasksbythemethodofdecisiontrees,whichareespecially"vulnerable"tousingthe"equivalent" structuresofknowledgerepresentationandtherulesforobtainingthetreenodes (Popova,2015;Popova, 2016;Popova, 2017;Popova, 2018a;Popova, 2018b). That is why the effect produced byautomatingsuchtasksshouldbegreaterthanoratleastequaltotheefficiencyofsolvingthem manually.Inthisarticle,letusanalyzeoneofsuchtasksandthewayofsolvingit.…”

Section: Introductionmentioning

confidence: 99%

Entropy and Algorithm of Obtaining Decision Trees in a Way Approximated to the Natural Intelligence

Popova

Popov

Karandey

et al. 2019

International Journal of Cognitive Informatics and Natural Intelligence

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The classification of knowledge of a specified subject area is an actual task. The well-known methods of obtaining decision trees using entropy are not suitable for the classification of the subject area knowledge. So, a new algorithm of obtaining decision trees, whose way of obtaining is approximated to the natural intelligence, is suggested in the article. Here, the knowledge of a subject area is presented as a complex of answers to questions, which help to find the solution to a current task. The connection of entropy with the appearance of knowledge, the classification of previous knowledge, and the definitions used in decision trees are also analyzed in the article. The latter is necessary to compare the suggested algorithm approximated to the natural intelligence with the traditional method, using a small example. The article contains the analysis of solving a classification task for such a subject area as optimization methods.

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“…Ранее О.Б. Поповой были выделены и исследованы основные этапы поискового исследования, автоматизирован процесс выбора [3,4]. в психологии и полученные О.Б.…”

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