This article provides an overview of some of the specialized datasets that were created for various projects related to the CiteSeer˟ digital library.

Article states that vaccines, though reliable preventative measures for diseases, also raise public concerns; public apprehension and doubts challenge the acceptance of new vaccines including the COVID-19 vaccines. This study is the first attempt to review the role of AI approaches in COVID-19 vaccination-related sentiment analysis.

This article reviews and summarizes the state-of-the-art methods and publicly available data sets from proximate sensing to support land-use analysis. Discussions highlight the challenges, strategies, and opportunities faced by the existing methods using proximate sensing imagery in urban land-use studies.

This paper discusses automatic generating of back-of-the-book indexes.

This article discusses motivating and retaining computer science students with a competitive game programming project.

Paper for the 2014 Association for Information Science and Technology (ASIS&T) Annual Meeting. This paper discusses building a collection of web archiving research articles.

Article exploring graph node property prediction. Originally presented as part of the application track at the 38th International Conference on Logic Programming in Haifa, Israel.

Article studying the problem of incorporating corpus, ontology, and semantic predications to learn the embeddings of MeSH terms. The authors propose a novel framework, Corpus, Ontology, and Semantic predications-based MeSH term embedding (COS), to generate high-quality MeSH term embeddings.

Article discussing the bacterial composition of subgingival plaque among diabetic and non-diabetic subjects to determine the effect that diabetes mellitus has on dental health.

This article develops a computational tool named Crinet to infer genome-wide ceRNA networks addressing critical drawbacks. Crinet-inferred ceRNA groups that were consistently involved in the immune system related processes could be important assets in the light of the studies confirming the relation between immunotherapy and cancer. The source code of Crinet is in R and available at https://github.com/bozdaglab/crinet.

This report discusses research on reducing our carbon footprint through ridesharing. The focus of this research project was to analyze and collect travel trajectories to calculate carbon footprints under different travel modes and identify ways to reduce it.

This article presents a novel approach of introducing a weighted temporal feature to bias a topic clustering toward articles in a similar time frame, performed over a set of finance journal abstracts from 1974 to 2020 to demonstrate how time can be emphasized in trend detection. The authors detect trending finance topics that are not identifiable when we use a standard clustering approach with no temporal bias.

This paper describes a co-training approach that uses the text and citation information of a research article as two different views to predict the topic of an article.

Paper from the Web-Scale Classification: Classifying Big Data from the Web Workshop. This paper proposes novel features that result in effective and efficient classification models for automatic identification of research articles.

This paper proposes PositionRank, an unsupervised model for keyphrase extraction from scholarly documents that incorporates information from all positions of a word's occurrences into a biased PageRank.

Article analyses the impact of Covid-19 on various cyber-security related aspects.

Article discussing word sense disambiguation with pattern learning and automatic feature selection.

This paper discusses intra-class competitive assignments in CS2.

This paper discusses linguistically motivated features for enhanced back-of-the-book indexing.

Article is a study proposing an approach for blood cancer disease prediction using the supervised machine learning approach to perform blood cancer prediction with high accuracy using microarray gene data.

This paper proposes a supervised model for keyphrase extraction from research papers, which are embedded in citation networks.

Article investigating HUMIRA effects mentioned in Twitter posts using a relational similarity-based method. The authors were able to identify effects previously known as well as potentially unreported, which demonstrates the power of this method and its potential for studying effects of other medications shared by Twitter users.

This technical report addresses how to hide secrets from an operating system. The authors provide a detailed design for the VM blackbox and some microarchitecture level simulation derived performance data. They also describe a compiler directed prefetch scheme that uses both instruction and data prefetches to obfuscate the address traces on the address bus between on-chip L2 cache and memory.

This article presents a study detecting Tweets that contain racist text by performing the sentiment analysis of Tweets. The proposed GCR-NN model can detect 97% of the tweets that contain racist comments.