Tourism has become one of the world’s largest service industries. Due to the rapid development of social media, more people like self-guided tours than package itineraries planned by travel agencies. Therefore, how to develop itinerary recommen...
In the era of big data, a significant volume of spatiotemporal data exists in a multiscale format, describing diverse phenomena in the objective world across different spatial and temporal scales. While existing methods focus on analyzing the feature...
To address the issue of low efficiency in source seeking within implicit information fields, this paper proposes an autonomous sourcing method based on a balanced search strategy inspired by biological homing behaviors. At the outset of the research,...
The existing knowledge graph embedding (KGE) method has achieved good performance in recommendation systems. However, the relevancy degree among entities reduces gradually along the spread in the knowledge graph. Focusing on the explicit and implicit...
The present review discusses the literature on how and when social category information and individuating information influence people’s implicit judgments of other individuals who belong to existing (i.e., known) social groups. After providing...
With users being exposed to the growing volume of online information, the recommendation system aiming at mining the important or interesting information is becoming a modern research topic. One approach of recommendation is to integrate the graph ne...
Graph neural networks (GNNs) have been highly successful in graph representation learning. The goal of GNNs is to enrich node representations by aggregating information from neighboring nodes. Much work has attempted to improve the quality of aggrega...
Considering the poor effect of short text classification due to insufficient semantic information mining in the current short text matching methods, a new short text classification method is proposed based on explicit and implicit multiscale weightin...
The main purpose of the joint entity and relation extraction is to extract entities from unstructured texts and extract the relation between labeled entities at the same time. At present, most existing joint entity and relation extraction networks ig...
Automated citation analysis is becoming increasingly important in assessing the scientific quality of publications and identifying patterns of collaboration among researchers. However, little attention has been paid to analyzing the scientific conten...
Implicit discourse relation recognition (IDRR) has long been considered a challenging problem in shallow discourse parsing. The absence of connectives makes such relations implicit and requires much more effort to understand the semantics of the text...
Georeferencing a kinematic Multi-Sensor-System (MSS) within crowded areas, such as inner-cities, is a challenging task that should be conducted in the most reliable way possible. In such areas, the Global Navigation Satellite System (GNSS) data eithe...
To provide more accurate and stable recommendations, it is necessary to combine display information with implicit information and to dig out potential information. Existing methods only consider explicit feedback information or implicit feedback info...
E-commerce systems experience poor quality of performance when the number of records in the customer database increases due to the gradual growth of customers and products. Applying implicit hidden features into the recommender system (RS) plays an i...
The most known and used abstract model of the financial market is based on the concept of the informational efficiency (EMH) of that market. The paper proposes an alternative which could be named the behavioural efficiency of the financial market, wh...
This paper reports the assessment of the infographics-value (IGV) short scale, designed to measure the value in the use of infographics. The scale was made to assess the implicit quality dimensions of infographics. These dimensions were experienced d...
Implicit causality (IC) is a phenomenon where verbs supply information about the potential cause of the behavior or state to one of the antecedents (e.g., “Mary praised David because…” will continue about David, not Mary). The stud...
Affective information is processed in different ways across one’s lifespan. Explanations for this pattern of performance are multiple and range from top-down motivational shifts and cognitive control to faster bottom-up and implicit processes....
Heterogeneous information network (HIN) embedding transforms multi-type nodes into low-dimensional vectors to preserve structural and semantic information for downstream tasks. However, it struggles with multiplex networks where nodes connect via div...
The implicit feedback information associated with actual behavior can symmetrically reflect consumer preference, which is valuable and deserves a deep investigation. Considering the inherent uncertainty and fuzziness of implicit data, the question of...
Post-traumatic Stress Disorder is a chronic condition that occurs following a traumatic experience. Information processing models of PTSD focus on integrating situationally triggered sensory-emotional memories with consciously accessible autobiograph...
Accurate and computationally efficient numerical modelling of shallow-water flows is essential for flood prediction and hydrodynamic risk assessment. This study develops an implicit finite-difference scheme for the numerical solution of the two-dimen...
Statistical learning (SL) is a method of learning based on the transitional probabilities embedded in sequential phenomena such as music and language. It has been considered an implicit and domain-general mechanism that is innate in the human brain a...
Crowdsensing data serves as a crucial resource for supporting spatiotemporal applications and services. However, its inherent heterogeneity and quality uncertainty present significant challenges for data usability assessment: the evaluation methods a...
Solving stiff partial differential equations with neural networks remains challenging due to the presence of multiple time scales and numerical instabilities that arise during training. This paper addresses these limitations by embedding the mathemat...
This paper examines the effectiveness of implicit beamforming (IBF), which enables transmission without channel state information (CSI) feedback in multi-user multiple-input multiple-output (MU-MIMO) systems with a large number of antennas. First, we...
Accurate climate data at fine spatial resolution are essential for scientific research and the development and planning of crucial social systems, such as energy and agriculture. Among them, sea surface temperature plays a critical role as the associ...
Packaging is no longer a mere structural element that only aims to preserve foods, but it is also a powerful marketing tool able to affect product perception, purchase decision and consumers’ food choices. Incorporating consumers’ voices...
Amid the growth of COVID-19 pandemic, SMEs are facing greater uncertainties and pressures to survive because even though they are efficiently managed, their human resource organizations lack a large number of resources and a well-developed training s...
To address challenges in state-of-health (SOH) estimation and remaining useful life (RUL) prediction for lithium-ion batteries under fast-charging conditions—strong nonlinear degradation, difficulty in explicit mechanism modeling, and unstable...
Most research on factors related to physical child abuse risk rely heavily on direct self-report measures, which is a methodological strategy susceptible to participant response distortions. Such methodological reliance obfuscates the interpretations...
Generative steganography (GS) generates stego-media via secret messages, but existing GS only targets single-type multimedia data with poor universality. The generator and extractor sizes are highly coupled with resolution. Message mapping converts s...
Implicit Motives are non-conscious needs that drive human behavior towards the achievement of incentives that are affectively incited. Repeated affective experiences providing satisfying rewards have been held responsible for the building of Implicit...
The field of sentiment analysis is currently dominated by the detection of attitudes in lexically explicit texts such as user reviews and social media posts. In objective text genres such as economic news, indirect expressions of sentiment are common...
Effective communication crucially depends on the ability to produce and recognize structured signals, as apparent in language and birdsong. Although it is not clear to what extent similar syntactic-like abilities can be identified in other animals, r...
Event cameras capture motion with high temporal resolution, but recovering from raw events a velocity field that also obeys the underlying flow physics remains difficult. Existing event-based methods either require ground-truth velocity or depth, whi...
Causal inference aims to faithfully depict the causal relationships between given variables. However, in many practical systems, variables are often partially observed, and some unobserved variables could carry significant information and induce caus...
Geological models are commonly used to represent geological structures in 3D space. A wide range of methods exists to create these models, with much scientific work focusing recently on implicit representation methods, which perform an interpolation...
Implicit sentiment identification is a significant classical task in text analysis. Graph neural networks (GNNs) have recently been successful in implicit sentiment identification, but the current approaches still suffer from two problems. On the one...
This article analyzes the risk contagion mechanism of local government implicit debt from the perspective of multi-subject collaboration, considering interaction effects among different influencing factors. On this basis, with the help of complex net...
This article addresses Croatian scholars’ information behavior and how they use technology to acquire information in three areas of their work: teaching, research, and administrative activities. Our study aims to find which communication channe...
Personalized recommendation has become indispensable in today’s information society. Personalized recommendations play a significant role for both information producers and consumers. Studies have shown that probability matrix factorization can...
This study explores explicit and implicit knowledge in large-scale linguistic data and digital footprints from social networks. This research aims to develop and test algorithms for analyzing both explicit and implicit information in user-generated c...
Aspect-based sentiment quadruple prediction has important application value in the current information age. There are often implicit expressions and multi-level semantic relationships in sentences, making accurate prediction for existing methods stil...
Generative models have shown excellent results in aspect-based sentiment analysis tasks by predicting quadruples by setting specific template formats. The existing research predicts sentiment elements and enhances the dependency between elements usin...
Implicit emotions are often expressed through implicit and weak clues between modalities due to the lack of explicit emotional feature words, representing a significant challenge for multimodal sentiment analysis. In order to improve implicit emotion...
Continuous implicit representations can flexibly describe complex 3D geometry and offer excellent potential for 3D point cloud analysis. However, it remains challenging for existing point-based deep learning architectures to leverage the implicit rep...
Public–private partnership (PPP) projects have the features of extended investment cycles, diminished returns, and high demand for technology. Inadequate utilization of these projects may result in an accumulation of new implicit debt for the g...
24 November 2021
Adolescence is a period where youngsters still do not know much about themselves. That makes some decisions, like those concerning vocational elections, a complicated issue that has important consequences for their life. The main goal of this piece o...
Business process outcome prediction plays an essential role in business process monitoring. It continuously analyzes completed process events to predict the executing cases’ outcome. Most of the current outcome prediction focuses only on the ac...
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