Information and knowledge management

Volunteer moderators are an increasingly essential component of effective community management across a range of services, such as Facebook, Reddit, Discord, YouTube, and Twitch. Prior work has investigated how users of these services become moderators, their attitudes towards community moderation, and the work that they perform, largely through interviews with community moderators and managers. In this

Product dimension is a crucial piece of information enabling customers make better buying decisions. Ecommerce websites extract dimension attributes to enable customers filter the search results according to their requirements. The existing methods extract dimension attributes from textual data like title and product description. However, this textual information often exists in an ambiguous, disorganized

Graph Neural Networks (GNNs) require that all nodes have initial representations which are usually derived from the node features. When the node features are absent, GNNs can learn node embeddings with an embedding layer or use pretrained network embeddings for the initial node representations. However, these approaches are limited because i) they cannot be easily extended to initialize new nodes that are

Sparsity of the data needed to learn about anomalies is often a key challenge faced when training deep supervised models for the task of Anomaly Detection (AD). Generating synthetic data by applying pre-determined transformations that conform to a set of known invariances has shown to improve performance of such deep models. In this work we present C-GATS to show that one can learn a much larger invariance

An important task for designing QA systems is answer sentence selection (AS2): selecting the sentence containing (or constituting) the answer to a question from a set of retrieved relevant documents. In this paper, we propose three novel sentence-level transformer pre-training objectives that incorporate paragraph-level semantics within and across documents, to improve the performance of transformers for