Now showing 1 - 10 of 27
  • Publication
    The UCD-Net System at SemEval-2020 Task 1: Temporal Referencing with Semantic Network Distances
    (International Committee for Computational Linguistics, 2020-12) ;
    This paper describes the UCD system entered for SemEval 2020 Task 1: Unsupervised Lexical Semantic Change Detection. We propose a novel method based on distance between temporally referenced nodes in a semantic network constructed from a combination of the time specific corpora. We argue for the value of semantic networks as objects for transparent exploratory analysis and visualisation of lexical semantic change, and present an implementation of a web application for the purpose of searching and visualising semantic networks. The results of the change measure used for this task were not among the best performing systems, but further calibration of the distance metric and backoff approaches may improve this method.
      10
  • Publication
    Hybrid agent & component-based management of backchannels
    This paper describes the use of the SoSAA software framework to implement the hybrid management of communication channels (backchannels) across a distributed software system. SoSAA is a new integrated architectural solution enabling context-aware, open and adaptive software while preserving system modularity and promoting the re-use of existing component-based and agent-oriented frameworks and associated methodologies. In particular, we show how SoSAA can be used to orchestrate the adoption of network adapter components to bind functional components that are distributed across different component contexts. Both the performance of the different computational nodes involved and the efficiencies and faults in the underlying transport layers are taken into account when deciding which transport mechanisms to use.
      432
  • Publication
    AF-ABLE in the Multi Agent Contest 2009
    This is the second year in which a team from University College Dublin has participated in the Multi Agent Contest. This paper describes the system that was created to participate in the contest, along with observations of the team's experiences in the contest. The system itself was built using the AFAPL agent programming language running on the Agent Factory platform. A hybrid control architecture inspired by the SoSAA strategy aided in the separation of concerns between low-level behaviours (such as movement and obstacle evasion) and higher-level planning and strategy.
      1149
  • Publication
    UCD-CS at W-NUT 2020 Shared Task-3: A Text to Text Approach for COVID-19 Event Extraction on Social Media
    (Association for Computational Linguistics, 2020-11-19) ;
    In this paper, we describe our approach in the shared task: COVID-19 event extraction from Twitter. The objective of this task is to extract answers from COVID-related tweets to a set of predefined slot-filling questions. Our approach treats the event extraction task as a question answering task by leveraging the transformer-based T5 text-to-text model. According to the official evaluation scores returned, namely F1, our submitted run achieves competitive performance compared to other participating runs (Top 3). However, we argue that this evaluation may underestimate the actual performance of runs based on text-generation. Although some such runs may answer the slot questions well, they may not be an exact string match for the gold standard answers. To measure the extent of this underestimation, we adopt a simple exact-answer transformation method aiming at converting the well-answered predictions to exactly-matched predictions. The results show that after this transformation our run overall reaches the same level of performance as the best participating run and state-of-the-art F1 scores in three of five COVID-related events. Our code is publicly available to aid reproducibility
      248
  • Publication
    Hierarchical Bloom Filter Trees for Approximate Matching
    (Journal of Digital Forensics, Security and Law, 2018-01) ; ;
    Bytewise approximate matching algorithms have in recent years shown significant promise in detecting files that are similar at the byte level. This is very useful for digital forensic investigators, who are regularly faced with the problem of searching through a seized device for pertinent data. A common scenario is where an investigator is in possession of a collection of "known-illegal" files (e.g. a collection of child abuse material) and wishes to find whether copies of these are stored on the seized device. Approximate matching addresses shortcomings in traditional hashing, which can only find identical files, by also being able to deal with cases of merged files, embedded files, partial files, or if a file has been changed in any way. Most approximate matching algorithms work by comparing pairs of files, which is not a scalable approach when faced with large corpora. This paper demonstrates the effectiveness of using a "Hierarchical Bloom Filter Tree" (HBFT) data structure to reduce the running time of collection-against-collection matching, with a specific focus on the MRSH-v2 algorithm. Three experiments are discussed, which explore the effects of different configurations of HBFTs. The proposed approach dramatically reduces the number of pairwise comparisons required, and demonstrates substantial speed gains, while maintaining effectiveness.
      374
  • Publication
    Current Challenges and Future Research Areas for Digital Forensic Investigation
    Given the ever-increasing prevalence of technology in modern life, there is a corresponding increase in the likelihood of digital devices being pertinent to a criminal investigation or civil litigation. As a direct consequence, the number of investigations requiring digital forensic expertise is resulting in huge digital evidence backlogs being encountered by law enforcement agencies throughout the world. It can be anticipated that the number of cases requiring digital forensic analysis will greatly increase in the future. It is also likely that each case will require the analysis of an increasing number of devices including computers, smartphones, tablets, cloud-based services, Internet of Things devices, wearables, etc. The variety of new digital evidence sources poses new and challenging problems for the digital investigator from an identification, acquisition, storage and analysis perspective. This paper explores the current challenges contributing to the backlog in digital forensics from a technical standpoint and outlines a number of future research topics that could greatly contribute to a more efficient digital forensic process.
      613
  • Publication
    An agent-based approach to component management
    (International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2009-05) ; ; ;
    This paper details the implementation of a software framework that aids the development of distributed and self-configurable software systems. This framework is an instance of a novel integration strategy called SoSAA (SOcially Situated Agent Architecture), which combines Component-Based Software Engineering and Agent-Oriented Software Engineering, drawing its inspiration from hybrid agent control architectures. The framework defines a complete construction process by enhancing a simple component-based framework with reasoning and self-awareness capabilities through a standardized interface. The capabilities of the resulting framework are demonstrated through its application to a non-trivial Multi Agent System (MAS). The system in question is a pre-existing Information Retrieval (IR) system that has not previously taken advantage of CBSE principles. In this paper we contrast these two systems so as to highlight the benefits of using this new hybrid approach. We also outline how component-based elements may be integrated into the Agent Factory agent-oriented application framework.
      4652
  • Publication
    Reflecting on Agent Programming with AgentSpeak(L)
    Agent-Oriented Programming (AOP) researchers have successfully developed a range of agent programming languages that bridge the gap between theory and practice. Unfortunately, despite the incommunity success of these languages, they have proven less compelling to the wider software engineering community. One of the main problems facing AOP language developers is the need to bridge the cognitive gap that exists between the concepts underpinning mainstream languages and those underpinning AOP. In this paper, we attempt to build such a bridge through a conceptual mapping that we subsequently use to drive the design of a new programming language entitled ASTRA, which has been evaluated by a group of experienced software engineers attending an Agent-Oriented Software Engineering Masters course.
      516
  • Publication
    EviPlant: An Efficient Digital Forensic Challenge Creation, Manipulation, and Distribution Solution
    (Elsevier, 2017-03-21) ; ;
    Education and training in digital forensics requires a variety of suitable challenge corpora containing realistic features including regular wear-and-tear, background noise, and the actual digital traces to be discovered during investigation. Typically, the creation of these challenges requires overly arduous effort on behalf of the educator to ensure their viability. Once created, the challenge image needs to be stored and distributed to a class for practical training. This storage and distribution step requires significant resources and time and may not even be possible in an online/distance learning scenario due to the data sizes involved. As part of this paper, we introduce a more capable methodology and system to current approaches. EviPlant is a system designed for the efficient creation, manipulation, storage and distribution of challenges for digital forensics education and training. The system relies on the initial distribution of base disk images, i.e., images containing solely bare operating systems. In order to create challenges for students, educators can boot the base system, emulate the desired activity and perform a diffing of resultant image and the base image. This diffing process extracts the modified artefacts and associated metadata and stores them in an evidence package. Evidence packages can be created for different personas, different wear-and-tear, different emulated crimes, etc., and multiple evidence packages can be distributed to students and integrated with the base images. A number of advantages and additional functionality over the current approaches are discussed that emerge as a result of using EviPlant.
      439Scopus© Citations 14
  • Publication
    MAMS: Multi-Agent MicroServices
    This paper explores the intersection between microservices and Multi-Agent Systems (MAS), introducing the notion of a new approach to building MAS known as Multi-Agent MicroServices (MAMS). Our approach is illustrated through a worked example of a Vickrey Auction implemented as a microservice.
    Scopus© Citations 32  25