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Found 13 papers, 3 papers with code
Association Rules Mining with Auto-Encoders
Classical association rule mining algorithms have several limitations, especially with regards to their high execution times and number of rules produced.
RISC: Generating Realistic Synthetic Bilingual Insurance Contract
RISC generates look-alike automobile insurance contracts based on the Quebec regulatory insurance form in French and English.
Relationship Between Online Harmful Behaviors and Social Network Message Writing Style
In this paper, we explore the relationship between an individual's writing style and the risk that they will engage in online harmful behaviors (such as cyberbullying).
Neural Bandits for Data Mining: Searching for Dangerous Polypharmacy
Polypharmacy, most often defined as the simultaneous consumption of five or more drugs at once, is a prevalent phenomenon in the older population.
Cambrian Explosion Algorithm for Multi-Objective Association Rules Mining
Association rule mining is one of the most studied research fields of data mining, with applications ranging from grocery basket problems to highly explainable classification systems.
Quantifying French Document Complexity
Measuring a document's complexity level is an open challenge, particularly when one is working on a diverse corpus of documents rather than comparing several documents on a similar topic or working on a language other than English.
A Novel Word Sense Disambiguation Approach Using WordNet Knowledge Graph
Unlike other algorithms, the SCSMM algorithm guarantees the capture of the maximum sentence context while maintaining the terms' order within the sentence.
Generating Intelligible Plumitifs Descriptions: Use Case Application with Ethical Considerations
Plumitifs (dockets) were initially a tool for law clerks.
Exploiting Non-Taxonomic Relations for Measuring Semantic Similarity and Relatedness in WordNet
Various applications in the areas of computational linguistics and artificial intelligence employ semantic similarity to solve challenging tasks, such as word sense disambiguation, text classification, information retrieval, machine translation, and document clustering.
Using Sentiment Information for Preemptive Detection of Toxic Comments in Online Conversations
The challenge of automatic detection of toxic comments online has been the subject of a lot of research recently, but the focus has been mostly on detecting it in individual messages after they have been posted.
Language Identification on Massive Datasets of Short Message using an Attention Mechanism CNN
We use this dataset to test several existing language identification systems, in order to obtain a set of coherent benchmarks, and we make our dataset publicly available so that others can add to this set of benchmarks.
Subversive Toxicity Detection using Sentiment Information
The presence of toxic content has become a major problem for many online communities.
Impact of Sentiment Detection to Recognize Toxic and Subversive Online Comments
The presence of toxic content has become a major problem for many online communities.
