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Articles 1 - 16 of 16
Full-Text Articles in Physical Sciences and Mathematics
Memory Network-Based Interpreter Of User Preferences In Content-Aware Recommender Systems, Nhu Thuat Tran, Hady W. Lauw
Memory Network-Based Interpreter Of User Preferences In Content-Aware Recommender Systems, Nhu Thuat Tran, Hady W. Lauw
Research Collection School Of Computing and Information Systems
This article introduces a novel architecture for two objectives recommendation and interpretability in a unified model. We leverage textual content as a source of interpretability in content-aware recommender systems. The goal is to characterize user preferences with a set of human-understandable attributes, each is described by a single word, enabling comprehension of user interests behind item adoptions. This is achieved via a dedicated architecture, which is interpretable by design, involving two components for recommendation and interpretation. In particular, we seek an interpreter, which accepts holistic user’s representation from a recommender to output a set of activated attributes describing user preferences. …
Graphsearchnet: Enhancing Gnns Via Capturing Global Dependencies For Semantic Code Search, Shangqing Liu, Xiaofei Xie, Jjingkai Siow, Lei Ma, Guozhu Meng, Yang Liu
Graphsearchnet: Enhancing Gnns Via Capturing Global Dependencies For Semantic Code Search, Shangqing Liu, Xiaofei Xie, Jjingkai Siow, Lei Ma, Guozhu Meng, Yang Liu
Research Collection School Of Computing and Information Systems
Code search aims to retrieve accurate code snippets based on a natural language query to improve software productivity and quality. With the massive amount of available programs such as (on GitHub or Stack Overflow), identifying and localizing the precise code is critical for the software developers. In addition, Deep learning has recently been widely applied to different code-related scenarios, ., vulnerability detection, source code summarization. However, automated deep code search is still challenging since it requires a high-level semantic mapping between code and natural language queries. Most existing deep learning-based approaches for code search rely on the sequential text ., …
Automating Defeasible Reasoning In Law With Answer Set Programming, How Khang Lim, Avishkar Mahajar, Martin Strecker, Meng Weng Wong
Automating Defeasible Reasoning In Law With Answer Set Programming, How Khang Lim, Avishkar Mahajar, Martin Strecker, Meng Weng Wong
Centre for Computational Law
The paper studies defeasible reasoning in rule-based systems, in particular about legal norms and contracts. We identify rule modifiers that specify how rules interact and how they can be overridden. We then define rule transformations that eliminate these modifiers, leading in the end to a translation of rules to formulas. For reasoning with and about rules, we contrast two approaches, one in a classical logic with SMT solvers, which is only briefly sketched, and one using non-monotonic logic with Answer Set Programming solvers, described in more detail.
Towards Cnl-Based Verbalization Of Computational Contracts, Inari Listenmaa, Maryam Hanafiah, Regina Cheong, Andreas Kallberg
Towards Cnl-Based Verbalization Of Computational Contracts, Inari Listenmaa, Maryam Hanafiah, Regina Cheong, Andreas Kallberg
Centre for Computational Law
We present a CNL, which is a component of L4, a domain-specific programming language for drafting laws and contracts. Along with formal verification, L4’s core functionalities include natural language generation. We present the NLG pipeline and an interactive process for ambiguity resolution.
An Efficient Transformer-Based Model For Vietnamese Punctuation Prediction, Hieu Tran, Cuong V. Dinh, Hong Quang Pham, Binh T. Nguyen
An Efficient Transformer-Based Model For Vietnamese Punctuation Prediction, Hieu Tran, Cuong V. Dinh, Hong Quang Pham, Binh T. Nguyen
Research Collection School Of Computing and Information Systems
In both formal and informal texts, missing punctuation marks make the texts confusing and challenging to read. This paper aims to conduct exhaustive experiments to investigate the benefits of the pre-trained Transformer-based models on two Vietnamese punctuation datasets. The experimental results show our models can achieve encouraging results, and adding Bi-LSTM or/and CRF layers on top of the proposed models can also boost model performance. Finally, our best model can significantly bypass state-of-the-art approaches on both the novel and news datasets for the Vietnamese language. It can gain the corresponding performance up to 21.45%21.45% and 18.27%18.27% in the overall F1-scores.
Convergence Of Media Attention Across 129 Countries, Jisun An, Hassan Aldarbesti, Haewoon Kwak
Convergence Of Media Attention Across 129 Countries, Jisun An, Hassan Aldarbesti, Haewoon Kwak
Research Collection School Of Computing and Information Systems
The objective of this study is to assess the longitudinal trends of media similarity and dissimilarity on the international scale. As news value has well-established political, cultural, and economic consequences, the degree to which media coverage and content is converging across countries has implications for international relations. To study this convergence, we use the daily data of the 100 topics that were over-reported in each country, compared to other countries, from March 7 to October 9, 2016. The results of this analysis indicate that two complementary patterns–globalization and domestication–explain the media attention across the countries. We conclude that this attention …
Large-Scale Online Feature Selection For Ultra-High Dimensional Sparse Data, Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu
Large-Scale Online Feature Selection For Ultra-High Dimensional Sparse Data, Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu
Research Collection School Of Computing and Information Systems
Feature selection (FS) is an important technique in machine learning and data mining, especially for large scale high-dimensional data. Most existing studies have been restricted to batch learning, which is often inefficient and poorly scalable when handling big data in real world. As real data may arrive sequentially and continuously, batch learning has to retrain the model for the new coming data, which is very computationally intensive. Online feature selection (OFS) is a promising new paradigm that is more efficient and scalable than batch learning algorithms. However, existing online algorithms usually fall short in their inferior efficacy. In this article, …
Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo
Revisiting Assert Use In Github Projects, Pavneet Singh Kochhar, David Lo
Research Collection School Of Computing and Information Systems
Assertions are often used to test the assumptions that developers have about a program. An assertion contains a boolean expression which developers believe to be true at a particular program point. It throws an error if the expression is not satisfied, which helps developers to detect and correct bugs. Since assertions make developer assumptions explicit, assertions are also believed to improve under-standability of code. Recently, Casalnuovo et al. analyse C and C++ programs to understand the relationship between assertion usage and defect occurrence. Their results show that asserts have a small effect on reducing the density of bugs and developers …
Period Decompositions For The Capacitated Lot Size Problem With Setup Times, Silvio Alexandre De Araujo, Bert De Reyck, Zeger Degraeve, Ioannis Fragkos, Raf Jans
Period Decompositions For The Capacitated Lot Size Problem With Setup Times, Silvio Alexandre De Araujo, Bert De Reyck, Zeger Degraeve, Ioannis Fragkos, Raf Jans
Research Collection Lee Kong Chian School Of Business
We study the multi-item capacitated lot sizing problem with setup times. Based on two strong reformulations of the problem, we present a transformed reformulation and valid inequalities that speed up column generation and Lagrange relaxation. We demonstrate computationally how both ideas enhance the performance of our algorithm and show theoretically how they are related to dual space reduction techniques. We compare several solution methods and propose a new efficient hybrid scheme that combines column generation and Lagrange relaxation in a novel way. Computational experiments show that the proposed solution method for finding lower bounds is competitive with textbook approaches and …
Creating The Park Cool Island In An Inner-City Neighborhood: Heat Mitigation Strategy For Phoenix, Az, Juan Declet-Barreto, Anthony J. Brazel, Chris A. Martin, Winston T. L. Chow, Sharon L. Harlan
Creating The Park Cool Island In An Inner-City Neighborhood: Heat Mitigation Strategy For Phoenix, Az, Juan Declet-Barreto, Anthony J. Brazel, Chris A. Martin, Winston T. L. Chow, Sharon L. Harlan
Research Collection School of Social Sciences
We conducted microclimate simulations in ENVI-Met 3.1 to evaluate the impact of vegetation in lowering temperatures during an extreme heat event in an urban core neighborhood park in Phoenix, Arizona. We predicted air and surface temperatures under two different vegetation regimes: existing conditions representative of Phoenix urban core neighborhoods, and a proposed scenario informed by principles of landscape design and architecture and Urban Heat Island mitigation strategies. We found significant potential air and surface temperature reductions between representative and proposed vegetation scenarios: 1) a Park Cool Island effect that extended to non-vegetated surfaces; 2) a net cooling of air underneath …
Enacting Clan Control In Complex It Projects: A Social Capital Perspective, Cecil Eng Huang Chua, Wee Kiat Lim, Christina Soh, Siew Kien Sia
Enacting Clan Control In Complex It Projects: A Social Capital Perspective, Cecil Eng Huang Chua, Wee Kiat Lim, Christina Soh, Siew Kien Sia
CMP Research
The information technology project control literature has documented that clan control is often essential in complex multistakeholder projects for project success. However, instituting clan control in such conditions is challenging as people come to a project with diverse skills and backgrounds. There is often insufficient time for clan control to develop naturally. This paper investigates the question , "How can clan control be enacted in complex IT projects? " Recognizing social capital as a resource , we conceptualize a clan as a group with strong social capital (i.e., where its members have developed their structural, cognitive, and relational ties to …
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu
Retrieval-Based Face Annotation By Weak Label Regularized Local Coordinate Coding, Dayong Wang, Steven C. H. Hoi, Ying He, Jianke Zhu
Research Collection School Of Computing and Information Systems
Retrieval-based face annotation is a promising paradigm in mining massive web facial images for automated face annotation. Such an annotation paradigm usually encounters two key challenges. The first challenge is how to efficiently retrieve a short list of most similar facial images from facial image databases, and the second challenge is how to effectively perform annotation by exploiting these similar facial images and their weak labels which are often noisy and incomplete. In this paper, we mainly focus on tackling the second challenge of the retrieval-based face annotation paradigm. In particular, we propose an effective Weak Label Regularized Local Coordinate …
Modeling 3d Articulated Motions With Conformal Geometry Videos (Cgvs), Dao T. P. Quynh, Ying He, Xiaoming Chen, Jiazhi Xia, Qian Sun, Steven C. H. Hoi
Modeling 3d Articulated Motions With Conformal Geometry Videos (Cgvs), Dao T. P. Quynh, Ying He, Xiaoming Chen, Jiazhi Xia, Qian Sun, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
3D articulated motions are widely used in entertainment, sports, military, and medical applications. Among various techniques for modeling 3D motions, geometry videos (GVs) are a compact representation in that each frame is parameterized to a 2D domain, which captures the 3D geometry (x, y, z) to a pixel (r, g, b) in the image domain. As a result, the widely studied image/video processing techniques can be directly borrowed for 3D motion. This paper presents conformal geometry videos (CGVs), a novel extension of the traditional geometry videos by taking into the consideration of the isometric nature of 3D articulated motions. We …
Intelligence Through Interaction: Towards A Unified Theory For Learning, Ah-Hwee Tan, Gail A. Carpenter, Stephen Grossberg
Intelligence Through Interaction: Towards A Unified Theory For Learning, Ah-Hwee Tan, Gail A. Carpenter, Stephen Grossberg
Research Collection School Of Computing and Information Systems
Machine learning, a cornerstone of intelligent systems, has typically been studied in the context of specific tasks, including clustering (unsupervised learning), classification (supervised learning), and control (reinforcement learning). This paper presents a learning architecture within which a universal adaptation mechanism unifies a rich set of traditionally distinct learning paradigms, including learning by matching, learning by association, learning by instruction, and learning by reinforcement. In accordance with the notion of embodied intelligence, such a learning theory provides a computational account of how an autonomous agent may acquire the knowledge of its environment in a real-time, incremental, and continuous manner. Through a …
Stochastic Dominance And Information Value, Young Koan Kwon, John C. Fellingham, D. Paul Newman
Stochastic Dominance And Information Value, Young Koan Kwon, John C. Fellingham, D. Paul Newman
Research Collection School Of Accountancy
Incentives for producing and disseminating information have been analysed in many different contexts. Kihlstrom [6], for example, develops a Bayesian framework to analyze the properties of demand functions for information about product quality. From an entirely different perspective, Spence [8, 91 demonstrates the private value of “signalling” information. Similarly, Wilson [lo] considers the value to the firm of producing technological information and the effect of such production on equilibrium theory.
Bounded Energy-Finite Solutions Of Delta U=Pu On A Riemannian Manifold, Young Koan Kwon, J. Schiff, L. Sario
Bounded Energy-Finite Solutions Of Delta U=Pu On A Riemannian Manifold, Young Koan Kwon, J. Schiff, L. Sario
Research Collection School Of Accountancy
The classification of Riemann surfaces with respect to the equation Δu = Pu (P^O, PΞ£ 0) was initiated by Ozawa [13] and further developed by L. Myrberg [8,9], Royden [14], Nakai [10,11], Sario-Nakai [15], Nakai-Sario [12], Glasner-Katz [3], and Kwon-Sario [7].