1,844 research outputs found
Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data
Semantic formalisms represent content in a uniform way according to ontologies. This enables manipulation and reasoning via automated means (e.g. Semantic Web services), but limits the user’s ability to explore the semantic data from a point of view that originates from knowledge representation motivations. We show how, for user consumption, a visualization of semantic data according to some easily graspable dimensions (e.g. space and time) provides effective sense-making of data. In this paper, we look holistically at the interaction between users and semantic data, and propose multiple visualization strategies and dynamic filters to support the exploration of semantic-rich data.
We discuss a user evaluation and how interaction challenges could be overcome to create an effective user-centred framework for the visualization and manipulation of semantic data. The approach has been implemented and evaluated on a real company archive
Natural language processing
Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems
A Factoid Question Answering System for Vietnamese
In this paper, we describe the development of an end-to-end factoid question
answering system for the Vietnamese language. This system combines both
statistical models and ontology-based methods in a chain of processing modules
to provide high-quality mappings from natural language text to entities. We
present the challenges in the development of such an intelligent user interface
for an isolating language like Vietnamese and show that techniques developed
for inflectional languages cannot be applied "as is". Our question answering
system can answer a wide range of general knowledge questions with promising
accuracy on a test set.Comment: In the proceedings of the HQA'18 workshop, The Web Conference
Companion, Lyon, Franc
Cloud-based Automatic Speech Recognition Systems for Southeast Asian Languages
This paper provides an overall introduction of our Automatic Speech
Recognition (ASR) systems for Southeast Asian languages. As not much existing
work has been carried out on such regional languages, a few difficulties should
be addressed before building the systems: limitation on speech and text
resources, lack of linguistic knowledge, etc. This work takes Bahasa Indonesia
and Thai as examples to illustrate the strategies of collecting various
resources required for building ASR systems.Comment: Published by the 2017 IEEE International Conference on Orange
Technologies (ICOT 2017
Digital content management of Heet Sib Sorng custom for semantic search
This research presents the results of the alteration knowledgeable following the instruction of the digital content management by semantic technology development. The boundary of this research consists of the integration of the opportunities provided by the existing ontology and two datasets with the resources having different contents, including the datasets from the central library, physical and electronic data, and the development of semantical web approaches in ontology. In this research, research and development methodology is used and the data were acquired through literature review. This research shows that the ontology and applications evaluated are high level, and that there is an inclination for integrated systems oriented towards digital content management in the Thai custom semantic search system, which finally bring to the convergence of linked data and knowledge-based system
User centred evaluation of a recommendation based image browsing system
In this paper, we introduce a novel approach to recommend images by mining user interactions based on implicit feedback of user browsing. The underlying hypothesis is that the interaction implicitly indicates the interests of the users for meeting practical image retrieval tasks. The algorithm mines interaction data and also low-level content of the clicked images to choose diverse images by clustering heterogeneous features. A user-centred, task-oriented, comparative evaluation was undertaken to verify the validity of our approach where two versions of systems { one set up to enable diverse image recommendation { the other allowing browsing only { were compared. Use was made of the two systems by users in simulated work task situations and quantitative and qualitative data collected as indicators of recommendation results and the levels of user's satisfaction. The responses from the users indicate that they nd the more diverse recommendation highly useful
Synergistic Interplay between Search and Large Language Models for Information Retrieval
Information retrieval (IR) plays a crucial role in locating relevant
resources from vast amounts of data, and its applications have evolved from
traditional knowledge bases to modern retrieval models (RMs). The emergence of
large language models (LLMs) has further revolutionized the IR field by
enabling users to interact with search systems in natural languages. In this
paper, we explore the advantages and disadvantages of LLMs and RMs,
highlighting their respective strengths in understanding user-issued queries
and retrieving up-to-date information. To leverage the benefits of both
paradigms while circumventing their limitations, we propose InteR, a novel
framework that facilitates information refinement through synergy between RMs
and LLMs. InteR allows RMs to expand knowledge in queries using LLM-generated
knowledge collections and enables LLMs to enhance prompt formulation using
retrieved documents. This iterative refinement process augments the inputs of
RMs and LLMs, leading to more accurate retrieval. Experiments on large-scale
retrieval benchmarks involving web search and low-resource retrieval tasks
demonstrate that InteR achieves overall superior zero-shot retrieval
performance compared to state-of-the-art methods, even those using relevance
judgment. Source code is available at https://github.com/Cyril-JZ/InteRComment: Pre-print. Work in progres
EVIA 2007: The First International Workshop on Evaluating Information Access (Workshop Report)
The first workshop on Evaluating Information Access was held at the National Institute of Informatics,
Tokyo, Japan on May 15th, 2007. It was composed of a five invited speakers and two sessions of refereed
papers and posters
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