Temporal intent is an important component of events. It plays an important role in collecting them from the web with focused crawlers. However, traditionally focused crawlers usually only consider factors such as topic keywords, web page content, and...
We study the problem of controllable citation text generation by introducing a new concept to generate citation texts. Citation text generation, as an assistive writing approach, has drawn a number of researchers’ attention. However, current re...
In this paper, we propose a new approach for recognizing intentions of humans by observing their activities with a color plus depth (RGB-D) camera. Activities and goals are modeled as a distributed network of inter-connected nodes in an Activation Sp...
Intent detection is one of the main tasks of a dialogue system. In this paper, we present our intent detection system that is based on fastText word embeddings and a neural network classifier. We find an improvement in fastText sentence vectorization...
12 August 2015
The goal of the present study was to examine whether intention type affects eye movement patterns in a change detection task In addition, we assessed whether the eye movement index could be used to identify human implicit intent. We attempted to gene...
In recent years, the civil aviation industry has actively promoted the automation and intelligence of control processes with the increasing use of various artificial intelligence technologies. Air–ground communication, as the primary means of i...
The evolving landscape of network systems necessitates automated tools for streamlined management and configuration. Intent-driven networking (IDN) has emerged as a promising solution for autonomous network management by prioritizing declaratively de...
Intent classification is an essential task for goal-oriented dialogue systems for automatically identifying customers’ goals. Although intent classification performs well in general settings, domain-specific user goals can still present a chall...
Internet of Vehicles (IoV) security mechanisms often classify isolated messages or assign node-level trust scores, yet these decisions do not explain whether a malicious but authenticated event has distorted the intended evolution of traffic. This pa...
This paper aims to uncover the generation patterns of pilot intentions during complex flight missions and to identify pilot intention states, thereby enabling airborne warning systems to understand and predict pilot intentions for early warning strat...
3 February 2022
The purpose of this study is to explore the beliefs, intentions, and influences that serve as barriers and facilitators to exclusive breastfeeding intent among Marshallese pregnant women in the United States (US). The study used a descriptive qualita...
Tool-level attacks on Large Language Model (LLM) agents—poisoned tool descriptions, prompt injection, and capability misrepresentation—are universally effective, yet no existing defense provides comprehensive protection. We propose Archit...
Intent recognition aims to identify users’ potential intents from their utterances, which is a key component in task-oriented dialog systems. A real challenge, however, is that the number of intent categories has grown faster than human-annotat...
Predicting target intent in complex, dynamic multi-agent environments remains a formidable challenge due to incomplete perception and the highly dynamic nature of multi-target interactions. Conventional approaches—such as D-S evidence theory, e...
The current virtual system for secondary school experiments poses several issues, such as limited methods of operation for students and an inability of the system to comprehend the users’ operational intentions, resulting in a greater operation...
Social media donation is an emerging sustainable business model. Donation in the context of social media can often bring benefits to content creators and social media platforms, as well as realizing their sustainable development. Based on attachment...
University accelerators are a recent but rapidly growing phenomenon that not only enhance regional entrepreneurial ecosystems but influence the success of university startups and regional development and prosperity. The aim of this research is to exp...
5 November 2021
To ensure human resource availability for a smooth response during various types of disasters, there is a need to improve the intent of those involved in responding to each hazard type. However, Disaster Medical Assistance Team personnel’s intent to...
This article reports the intent to receive a SARS-COV-2 vaccine, its predictors and willingness to pay in Bangladesh. We carried out an online cross-sectional survey of 697 adults from the general population of Bangladesh in January 2021. A structure...
The interrelatedness of social-structural aspects and psychological features with vaccination intention provides the context to explore personal psychological features related to vaccination. Specifically, we focused on general decision making and va...
As autonomous vehicles become more common on the roads, their advancement draws on safety concerns for vulnerable road users, such as pedestrians and cyclists. This paper presents a review of recent developments in pedestrian and cyclist detection an...
To address the limitations of existing vehicle trajectory prediction methods, including insufficient modeling of dynamic inter-vehicle interactions, weak temporal continuity of complex driving intentions such as lane-changing, and high uncertainty in...
Session-based recommendation (SBR) aims to predict potential user interactions within an anonymous session. It utilizes learned user interests to recommend items. As research has progressed, researchers have shifted towards exploring user initial int...
25 August 2021
The aim of this study was to evaluate (1) the female medical students’ knowledge about HPV infection; (2) the associations between the HPV vaccination intent and coping strategies, health locus of control (HLOC), and sense of coherence; and (3) the s...
This study investigates the factors that contribute to veterinary professionals’ intentions to intervene in cases of suspected animal abuse. A survey was distributed to students, faculty, and staff in two Veterinary Medicine programs. Factors a...
Background/Objective: Transformational leadership (TL) by nurse managers is a modifiable organizational factor consistently linked to improved staff outcomes. However, evidence from the Arab Gulf region, particularly the Kingdom of Saudi Arabia (KSA)...
In an anonymous session recommendation scenario, the key to predicting the user’s next interaction item is accurately recognizing the user’s intent. Traditional methods focusing on the item Identity Document (ID) modeling have limitations...
Since understanding a user’s request has become a critical task for the artificial intelligence speakers, capturing intents and finding correct slots along with corresponding slot value is significant. Despite various studies concentrating on a...
In the short term, a fully autonomous level of machine intelligence cannot be achieved. Humans are still an important part of HCI systems, and intelligent systems should be able to “feel” and “predict” human intentions in orde...
Intent detection and slot filling are important modules in task-oriented dialog systems. In order to make full use of the relationship between different modules and resource sharing, solving the problem of a lack of semantics, this paper proposes a m...
Detecting the communicative intent behind user queries is critically required by search engines to understand a user’s search goal and retrieve the desired results. Due to increased web searching in local languages, there is an emerging need to...
Background/Objectives: The increasing rates of nurse turnover pose significant challenges to healthcare systems, negatively impacting patient outcomes and increasing operational costs. Despite the recognized importance of retaining nursing staff, fac...
Computational linguistics explores how human language is interpreted automatically and then processed. Research in this area takes the logical and mathematical features of natural language and advances methods and statistical procedures for automated...
Walking in real-world environments involves constant decision-making, e.g., when approaching a staircase, an individual decides whether to engage (climbing the stairs) or avoid. For the control of assistive robots (e.g., robotic lower-limb prostheses...
Chatbots are becoming increasingly popular and require the ability to interpret natural language to provide clear communication with humans. To achieve this, intent detection is crucial. However, current applications typically need a significant amou...
With the advancement of intelligent human–computer interaction (IHCI) technology, the accurate recognition of an operator’s intent has become essential for improving the collaborative efficiency in complex tasks. To address the challenges...
Intent sensing—the ability to sense what a user wants to happen—has many potential technological applications. Assistive medical devices, such as prosthetic limbs, could benefit from intent-based control systems, allowing for faster and m...
Successful applications of deep learning technologies in the natural language processing domain have improved text-based intent classifications. However, in practical spoken dialogue applications, the users’ articulation styles and background n...
Code coverage-guided unit test generation (CGTG) and large language model-based test generation (LLMTG) are two principal approaches for the generation of unit tests. Each of these approaches has its inherent advantages and drawbacks. Tests generated...
Sequential recommendations seek to predict the next item a user will interact with by modeling historical behavior, yet most approaches emphasize either temporal dynamics or item relationships and thus miss how structural co-intents interact with dyn...
Platform support for mobile collaboration among multiple smart devices has been an active research issues in the computing community. Using platform-level collaboration functionalities, a mobile device can share its resources, I/O events, and even ap...
Current travel planning tools suffer from information fragmentation, requiring users to switch between multiple apps for maps, weather, hotels, and other services, which creates a disjointed user experience. While Large Language Models (LLMs) show pr...
Proactive lane-change risk assessment requires estimating whether an intended maneuver will lead to unsafe interactions before the maneuver is completed. This is challenging in naturalistic driving data because actual crashes are extremely rare, and...
Natural language understanding (NLU) is an important aspect of achieving human–machine interactions in the automotive application field, consisting of two core subtasks, multiple-intent detection, and slot filling (ID-SF). However, existing joi...
In Industry 4.0 environments, operators and production managers frequently query industrial databases for production monitoring, quality control, and equipment maintenance using natural language. Existing Chinese NL2SQL systems often process semantic...
The Sexual Intent Perceptions Questionnaire (SIP-Q) is a 25-item instrument designed to measure interpretations of women’s sexual willingness communicated via various behaviors. The instrument demonstrates high internal consistency using a 7-po...
Out-of-Domain (OOD) intent classification is an important task for a dialog system, as it allows for appropriate responses to be generated. Previous studies aiming to solve the OOD intent classification task have generally adopted metric learning met...
Recent applications of wearable inertial measurement units (IMUs) for predicting human movement have often entailed estimating action-level (e.g., walking, running, jumping) and joint-level (e.g., ankle plantarflexion angle) motion. Although action-l...
Intent detection and slot filling tasks share common semantic features and are interdependent. The abundance of professional terminology in specific domains, which poses difficulties for entity recognition, subsequently impacts the performance of int...
Breast cancer is the most commonly diagnosed malignancy in women, with triple-negative breast cancer (TNBC) accounting for 10–20% of cases. Historically, fewer treatment options have existed for this subtype of breast cancer, with cytotoxic che...
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