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Neural networks are a revolutionary but immature technique that is fast evolving and heavily relies on data. To benefit from the newest development and newly available data, we want the gap between research and production as small as…
The ACL Anthology is an online repository that serves as a comprehensive collection of publications in the field of natural language processing (NLP) and computational linguistics (CL). This paper presents a tool called ``ACL Anthology…
The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmented and unstructured knowledge organization impedes deep interdisciplinary integration.…
Large-scale data sets on scholarly publications are the basis for a variety of bibliometric analyses and natural language processing (NLP) applications. Especially data sets derived from publication's full-text have recently gained…
The task of clustering a set of objects based on multiple sources of data arises in several modern applications. We propose an integrative statistical model that permits a separate clustering of the objects for each data source. These…
This survey focuses on intrusion detection systems (IDS) that leverage host-based data sources for detecting attacks on enterprise network. The host-based IDS (HIDS) literature is organized by the input data source, presenting targeted…
Effective data management and sharing are critical success factors in industry-academia collaboration. This paper explores the motivations and lessons learned from publishing open data sets in such collaborations. Through a survey of…
A method is described to empower students to efficiently perform general and literature searches using online resources. The method was tested on undergraduate and graduate students with varying backgrounds with scientific literature.…
We present WISER, a new semantic search engine for expert finding in academia. Our system is unsupervised and it jointly combines classical language modeling techniques, based on text evidences, with the Wikipedia Knowledge Graph, via…
The field of scientometrics has shown the power of citation-based clusters for literature analysis, yet this technique has barely been used for information retrieval tasks. This work evaluates the performance of citation based-clusters for…
The launch of Google Scholar (GS) marked the beginning of a revolution in the scientific information market. This search engine, unlike traditional databases, automatically indexes information from the academic web. Its ease of use,…
This paper describes an information system designed to support the large volume of monitoring information generated by a distributed testbed. This monitoring information is produced by several subsystems and consists of status and…
We are presenting a text analysis tool set that allows analysts in various fields to sieve through large collections of multilingual news items quickly and to find information that is of relevance to them. For a given document collection,…
The aim of the Canadian publications in Library and Information Science (LIS) database is to help break down the silos in which the two main target audiences - LIS faculty members and academic librarians - conduct their research. As part of…
The web application presented in this paper allows for an analysis to reveal centres of excellence in different fields worldwide using publication and citation data. Only specific aspects of institutional performance are taken into account…
We present an open-source Python library for building and using datasets where inputs are clusters of textual data, and outputs are sequences of real values representing one or more time series signals. The news-signals library supports…
Discovering and making sense of relevant literature is fundamental in any scientific field. Node-link diagram-based visualization tools can aid this process; however, existing tools have been evaluated only on small scales. This paper…
Information access systems such as search engines and generative AI are central to how people seek, evaluate, and interpret information. Yet most systems are designed to optimise retrieval rather than to help users develop better search…
Systematic reviews (SRs) - the librarian-assisted literature survey of scholarly articles takes time and requires significant human resources. Given the ever-increasing volume of published studies, applying existing computing and…
Datasets in the computer vision academic research community are primarily static. Once a dataset is accepted as a benchmark for a computer vision task, researchers working on this task will not alter it in order to make their results…