Matches in SemOpenAlex for { <https://semopenalex.org/work/W3196286742> ?p ?o ?g. }
Showing items 1 to 73 of
73
with 100 items per page.
- W3196286742 endingPage "4005" @default.
- W3196286742 startingPage "3996" @default.
- W3196286742 abstract "Data Mining is the technology that blends the traditional Data Analysis method with the sophisticated algorithms for processing large amount of data. Recommendation system enables the ability to use the various types of user-preference and user-requirement data to make recommendation. There many issues faced by the recommendation system among that major issue is that they need large data to effective make the recommendations. The main problems that are raised are changing the data, changing user preferences and unpredictable items. To overcome, in the proposed work High Average-Utility Mining is used. The two Deep learning techniques namely Recurrent Neural Network and fusion of Recurrent Neural Network-Convolutional Neural Network have been used. For this, dataset have been obtained from online of super market. For preprocessing, normalization is done on the actual dataset followed Long Format Data Frame is implemented to find the High Average Utility Itemset Mining. The preprocessed data is given as the input to Convolutional Neural Network which is activated by the sigmoid function. On the other hand the sigmoid Function is replaced with Recurrent Neural Network. 2-Bidirectinal LSTM is used which classifies the Predicted Products and the top k recommended products. From the above experiments, it is found that CNN-RNN fusion model gives the satisfactory results." @default.
- W3196286742 created "2021-08-30" @default.
- W3196286742 creator A5007636397 @default.
- W3196286742 creator A5041880497 @default.
- W3196286742 date "2021-08-25" @default.
- W3196286742 modified "2023-09-26" @default.
- W3196286742 title "Recommendation System for High Average Utility Itemset using Deep Learning Techniques" @default.
- W3196286742 hasPublicationYear "2021" @default.
- W3196286742 type Work @default.
- W3196286742 sameAs 3196286742 @default.
- W3196286742 citedByCount "0" @default.
- W3196286742 crossrefType "journal-article" @default.
- W3196286742 hasAuthorship W3196286742A5007636397 @default.
- W3196286742 hasAuthorship W3196286742A5041880497 @default.
- W3196286742 hasConcept C10551718 @default.
- W3196286742 hasConcept C108583219 @default.
- W3196286742 hasConcept C119857082 @default.
- W3196286742 hasConcept C124101348 @default.
- W3196286742 hasConcept C136886441 @default.
- W3196286742 hasConcept C144024400 @default.
- W3196286742 hasConcept C147168706 @default.
- W3196286742 hasConcept C154945302 @default.
- W3196286742 hasConcept C19165224 @default.
- W3196286742 hasConcept C34736171 @default.
- W3196286742 hasConcept C41008148 @default.
- W3196286742 hasConcept C50644808 @default.
- W3196286742 hasConcept C557471498 @default.
- W3196286742 hasConcept C81363708 @default.
- W3196286742 hasConcept C81388566 @default.
- W3196286742 hasConceptScore W3196286742C10551718 @default.
- W3196286742 hasConceptScore W3196286742C108583219 @default.
- W3196286742 hasConceptScore W3196286742C119857082 @default.
- W3196286742 hasConceptScore W3196286742C124101348 @default.
- W3196286742 hasConceptScore W3196286742C136886441 @default.
- W3196286742 hasConceptScore W3196286742C144024400 @default.
- W3196286742 hasConceptScore W3196286742C147168706 @default.
- W3196286742 hasConceptScore W3196286742C154945302 @default.
- W3196286742 hasConceptScore W3196286742C19165224 @default.
- W3196286742 hasConceptScore W3196286742C34736171 @default.
- W3196286742 hasConceptScore W3196286742C41008148 @default.
- W3196286742 hasConceptScore W3196286742C50644808 @default.
- W3196286742 hasConceptScore W3196286742C557471498 @default.
- W3196286742 hasConceptScore W3196286742C81363708 @default.
- W3196286742 hasConceptScore W3196286742C81388566 @default.
- W3196286742 hasLocation W31962867421 @default.
- W3196286742 hasOpenAccess W3196286742 @default.
- W3196286742 hasPrimaryLocation W31962867421 @default.
- W3196286742 hasRelatedWork W1838058638 @default.
- W3196286742 hasRelatedWork W2791521493 @default.
- W3196286742 hasRelatedWork W2802102212 @default.
- W3196286742 hasRelatedWork W2806278221 @default.
- W3196286742 hasRelatedWork W2900841426 @default.
- W3196286742 hasRelatedWork W2902690839 @default.
- W3196286742 hasRelatedWork W2939931462 @default.
- W3196286742 hasRelatedWork W2943854869 @default.
- W3196286742 hasRelatedWork W2952198026 @default.
- W3196286742 hasRelatedWork W2981927672 @default.
- W3196286742 hasRelatedWork W3003646942 @default.
- W3196286742 hasRelatedWork W3036728865 @default.
- W3196286742 hasRelatedWork W3097529015 @default.
- W3196286742 hasRelatedWork W3110108398 @default.
- W3196286742 hasRelatedWork W3111513472 @default.
- W3196286742 hasRelatedWork W3166227554 @default.
- W3196286742 hasRelatedWork W3172107828 @default.
- W3196286742 hasRelatedWork W3176080685 @default.
- W3196286742 hasRelatedWork W3189478000 @default.
- W3196286742 hasRelatedWork W3200304555 @default.
- W3196286742 isParatext "false" @default.
- W3196286742 isRetracted "false" @default.
- W3196286742 magId "3196286742" @default.
- W3196286742 workType "article" @default.