Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Self-Attention Bidirectional Long Short-Term Memory for Cold Start Movie Recommendation Models Subject The topic of the resource Bidirectional Long Short-Term Memory; Lemmatization; Movie recommendation; Self-attention; Stemming; Term frequency-inverse document frequency Description An account of the resource Movie recommendation systems are useful tools that help users find relevant results and prevent information overload. On the other hand, the user cold-start issue has arisen because the system lacks sufficient user data. Furthermore, they are not very scalable for use in extensive real-world applications. One of the key strategies to address the sparsity and cold-start problems is to leverage other sources of information, including item or user profiles or user reviews. Processing client feedback is typically a challenging process that involves challenging the interpretation and analysis of the textual data. Thus, this research implements an efficient deep learning-based recommendation architecture. Following the acquisition of textual data from the Amazon product reviews database, stop word removal, lemmatization, and stemming techniques are applied to the data pre-processing which eliminate inconsistent and redundant data, facilitating the process of interpreting and utilising data. Then, the Term Frequency-Inverse Document Frequency (TF-IDF) method is applied to extract the feature values from the pre-processed text data. The extracted feature values are fed to the Self-Attention Bidirectional Long Short-Term Memory (SA-BiLSTM) that utilises the matrix factorization method framework's information sources. The SA-BiLSTM model obtained 95.93% of recall, 94.76% of precision, and 97.84% of accuracy on the amazon product reviews database. 2023 IEEE. Creator An entity primarily responsible for making the resource Manohar M.; Reddy R.A.; Alzubaidi L.H.; Hameed Abdul Hussein A.; Buvaneswari P.R. Source A related resource from which the described resource is derived IEEE 1st International Conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023 Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/AIKIIE60097.2023.10390324" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AIKIIE60097.2023.10390324</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187286422&amp;doi=10.1109%2FAIKIIE60097.2023.10390324&amp;partnerID=40&amp;md5=6c63a1f8bcf2d90f89fe34808d767193" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187286422&amp;doi=10.1109%2fAIKIIE60097.2023.10390324&amp;partnerID=40&amp;md5=6c63a1f8bcf2d90f89fe34808d767193</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835031646-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Manohar M., Christ (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Reddy R.A., School of Computer Science and Artificial Intelligence, Sr University, Warangal, India; Alzubaidi L.H., The Islamic University, Najaf, Iraq; Hameed Abdul Hussein A., College of Pharmacy Ahl Al Bayt University, Karbala, Iraq; Buvaneswari P.R., School of Electrical and Electronic Engineering Vit Bhopal University, Sehhore, India