scholarly journals Spoken dialogue BIM systems – an application of big data in construction

Facilities ◽  
2017 ◽  
Vol 35 (13/14) ◽  
pp. 787-800 ◽  
Author(s):  
Ibrahim Motawa
Keyword(s):  
Big Data ◽  
Rapid Development ◽  
High Volume ◽  
Case Based Reasoning ◽  
Dialogue System ◽  
Spoken Dialogue Systems ◽  
Spoken Dialogue ◽  
Content Type ◽  
Building Maintenance ◽  
Operation Knowledge

Purpose With the rapid development in the internet technologies, the applications of big data in construction have seen considerable attention. Currently, there are many input/output modes of capturing construction knowledge related to all construction stages. On the other hand, building information modelling (BIM) systems have been developed to help in storing various structured data of buildings. However, these systems cannot fully capture the knowledge and unstructured data used in the operation of building systems in a usable format that uses the intelligent capabilities of BIM systems. Therefore, this research aims to adopt the concept of big data and develop a spoken dialogue BIM system to capture buildings operation knowledge, particularly for building maintenance and refurbishment. Design/methodology/approach The proposed system integrates cloud-based spoken dialogue system and case-based reasoning BIM system. Findings The system acts as an interactive expert agent that seeks answers from the user for questions specific to building maintenance problems and helps searching for solutions from previously stored knowledge cases. The practices of monitoring and maintaining buildings performance can be more efficient by the retrieval of relevant solutions from the captured knowledge to new problems when maintaining buildings components. The developed system enables easier capture and search for solutions to new problems with a more comprehensive retrieval of information. Originality/value Capturing multi-modes data into BIM systems using the cloud-based spoken dialogue systems will help construction teams use the high volume of data generated over building lifecycle and search for the most suitable solutions for maintenance problems. This new area of research also contributes to the current BIM systems by advancing their capabilities to instantly capture and retrieve knowledge of operations instead of only information.

scholarly journals Characterizing and Predicting Corrections in Spoken Dialogue Systems

2006 ◽  
Vol 32 (3) ◽  
pp. 417-438 ◽  
Author(s):  
Diane Litman ◽  
Julia Hirschberg ◽  
Marc Swerts
Keyword(s):  
Speech Recognition ◽  
Predictive Power ◽  
Classification Error ◽  
Dialogue Systems ◽  
Dialogue System ◽  
Spoken Dialogue Systems ◽  
Experimental Conditions ◽  
Spoken Dialogue ◽  
Spoken Dialogue System ◽  
Recognition Errors

This article focuses on the analysis and prediction of corrections, defined as turns where a user tries to correct a prior error made by a spoken dialogue system. We describe our labeling procedure of various corrections types and statistical analyses of their features in a corpus collected from a train information spoken dialogue system. We then present results of machine-learning experiments designed to identify user corrections of speech recognition errors. We investigate the predictive power of features automatically computable from the prosody of the turn, the speech recognition process, experimental conditions, and the dialogue history. Our best-performing features reduce classification error from baselines of 25.70–28.99% to 15.72%.

Bibliometric analysis and critical review of the research on big data in the construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yusheng Lu ◽  
Jiantong Zhang
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Bibliometric Analysis ◽  
Critical Review ◽  
Rapid Development ◽  
Heterogeneous Data ◽  
The Body ◽  
Future Research ◽  
Temporal And Spatial Distribution ◽  
Content Type

PurposeThe digital revolution and the use of big data (BD) in particular has important applications in the construction industry. In construction, massive amounts of heterogeneous data need to be analyzed to improve onsite efficiency. This article presents a systematic review and identifies future research directions, presenting valuable conclusions derived from rigorous bibliometric tools. The results of this study may provide guidelines for construction engineering and global policymaking to change the current low-efficiency of construction sites.Design/methodology/approachThis study identifies research trends from 1,253 peer-reviewed papers, using general statistics, keyword co-occurrence analysis, critical review, and qualitative-bibliometric techniques in two rounds of search.FindingsThe number of studies in this area rapidly increased from 2012 to 2020. A significant number of publications originated in the UK, China, the US, and Australia, and the smallest number from one of these countries is more than twice the largest number in the remaining countries. Keyword co-occurrence is divided into three clusters: BD application scenarios, emerging technology in BD, and BD management. Currently developing approaches in BD analytics include machine learning, data mining, and heuristic-optimization algorithms such as graph convolutional, recurrent neural networks and natural language processes (NLP). Studies have focused on safety management, energy reduction, and cost prediction. Blockchain integrated with BD is a promising means of managing construction contracts.Research limitations/implicationsThe study of BD is in a stage of rapid development, and this bibliometric analysis is only a part of the necessary practical analysis.Practical implicationsNational policies, temporal and spatial distribution, BD flow are interpreted, and the results of this may provide guidelines for policymakers. Overall, this work may develop the body of knowledge, producing a reference point and identifying future development.Originality/valueTo our knowledge, this is the first bibliometric review of BD in the construction industry. This study can also benefit construction practitioners by providing them a focused perspective of BD for emerging practices in the construction industry.

scholarly journals Spoken Dialogue System: Its Applications in the Developing Countries and a Technology for Bridging the Digital Divide and Augmenting Scarce Services in those Countries

2019 ◽  
pp. 1-11
Author(s):  
Oyelami Olufemi Moses
Keyword(s):  
Developing Countries ◽  
Digital Divide ◽  
Developing World ◽  
Developing Nations ◽  
Dialogue Systems ◽  
Dialogue System ◽  
Spoken Dialogue Systems ◽  
Spoken Dialogue ◽  
Spoken Dialogue System ◽  
The World

Aims: This article reports the various application areas of the spoken dialogue system in the developing world to determine if the system could be used to bridge the digital divide prevalent in these regions of the world. The work also aims to identify in which developing nations is the system currently being put to use. Study Design:  A survey of twenty articles on the subject matter was carried out and their domains of the application were identified. The different forms of the evaluation carried out on them were also identified towards determining their outcomes positivity for bridging the digital divide. Various comments made of the different evaluations were also considered in determining the suitability of spoken dialogue systems in bridging the digital divide. Place and Duration of Study: Department of Computer Science and Information Technology, Bowen University, Iwo, Nigeria, between February 2013 and October 2019. Methodology: The different domains of the works, the different forms of the evaluation carried out on the systems, the various comments consequent upon the testing of the systems by the participants and the developing countries where those works were carried out were identified. A position was now taken based on the results obtained.   Results: Nine of the works are in the healthcare domain, three in agriculture, one in banking, one in aviation, one in secretarial work, one in the accuracy of recognition, one in education and three having multiple domains. The various comments and results from the evaluations all point towards the system’s suitability for bridging the digital divide. The spoken dialogue system is currently being used in only six developing nations of the world. Conclusion: Consequent upon the results obtained, it is clear that spoken dialogue systems can be used to bridge the digital divide in the developing world and that other application areas not yet covered could be explored for the benefits of the citizens of these regions, especially the digitally disadvantaged ones.

Supply chain sales forecasting based on lightGBM and LSTM combination model

2019 ◽  
Vol 120 (2) ◽  
pp. 265-279 ◽  
Author(s):  
Tingyu Weng ◽  
Wenyang Liu ◽  
Jun Xiao
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
High Efficiency ◽  
Rapid Development ◽  
Data Sets ◽  
Production Environment ◽  
Content Type ◽  
Temporal Features ◽  
High Level

Purpose The purpose of this paper is to design a model that can accurately forecast the supply chain sales. Design/methodology/approach This paper proposed a new model based on lightGBM and LSTM to forecast the supply chain sales. In order to verify the accuracy and efficiency of this model, three representative supply chain sales data sets are selected for experiments. Findings The experimental results show that the combined model can forecast supply chain sales with high accuracy, efficiency and interpretability. Practical implications With the rapid development of big data and AI, using big data analysis and algorithm technology to accurately forecast the long-term sales of goods will provide the database for the supply chain and key technical support for enterprises to establish supply chain solutions. This paper provides an effective method for supply chain sales forecasting, which can help enterprises to scientifically and reasonably forecast long-term commodity sales. Originality/value The proposed model not only inherits the ability of LSTM model to automatically mine high-level temporal features, but also has the advantages of lightGBM model, such as high efficiency, strong interpretability, which is suitable for industrial production environment.

Case-based reasoning and BIM systems for asset management

2015 ◽  
Vol 5 (3) ◽  
pp. 233-247 ◽  
Author(s):  
Ibrahim Motawa ◽  
Abdulkareem Almarshad
Keyword(s):  
Asset Management ◽  
Information Exchange ◽  
Relevant Information ◽  
Integrated System ◽  
Case Based Reasoning ◽  
Content Type ◽  
Building Maintenance ◽  
Building Models ◽  
Building Information ◽  
Case Based

Purpose – The next generation of Building Information Modelling (BIM) seeks to establish the concept of Building Knowledge Modelling (BKM). The current BIM applications in construction, including those for asset management, have been mainly used to ensure consistent information exchange among the stakeholders. However, BKM needs to utilise knowledge management (KM) techniques into building models to advance the use of these systems. The purpose of this paper is to develop an integrated system to capture, retrieve, and manage information/knowledge for one of the key operations of asset management: building maintenance (BM). Design/methodology/approach – The proposed system consists of two modules; BIM module to capture relevant information and case-based reasoning (CBR) module to capture the operational knowledge of maintenance activities. The structure of the CBR module was based on analysis of a number of interviews and case studies conducted with professionals working in public BM departments. This paper discusses the development of the CBR module and its integration with the BIM module. The case retaining function of the developed system identifies the information/knowledge relevant to maintenance cases and pursues the related affected building elements by these cases. Findings – The paper concludes that CBR as a tool for KM can improve the performance of BIM models. Originality/value – As the research in BKM is still relatively immature, this research takes an advanced step by incorporating the intelligent functions of knowledge systems into BIM-based systems which helps the transformation from the conventional BIM to BKM.

scholarly journals Robust grammatical analysis for spoken dialogue systems

1999 ◽  
Vol 5 (1) ◽  
pp. 45-93 ◽  
Author(s):  
GERTJAN VAN NOORD ◽  
GOSSE BOUMA ◽  
ROB KOELING ◽  
MARK-JAN NEDERHOF
Keyword(s):  
Viable Alternative ◽  
Dialogue Systems ◽  
Test Results ◽  
Sources Of Information ◽  
Dialogue System ◽  
Spoken Dialogue Systems ◽  
Spoken Dialogue ◽  
Spoken Dialogue System ◽  
Grammatical Analysis ◽  
Robust Parsing

We argue that grammatical analysis is a viable alternative to concept spotting for processing spoken input in a practical spoken dialogue system. We discuss the structure of the grammar, and a model for robust parsing which combines linguistic sources of information and statistical sources of information. We discuss test results suggesting that grammatical processing allows fast and accurate processing of spoken input.

scholarly journals Automatically Training a Problematic Dialogue Predictor for a Spoken Dialogue System

2002 ◽  
Vol 16 ◽  
pp. 293-319 ◽  
Author(s):  
M. A. Walker ◽  
I. Langkilde-Geary ◽  
H. Wright Hastie ◽  
J. Wright ◽  
A. Gorin
Keyword(s):  
Information Sources ◽  
Dialogue Systems ◽  
Dialogue System ◽  
Spoken Dialogue Systems ◽  
Spoken Dialogue ◽  
Spoken Dialogue System ◽  
Customer Care ◽  
Dialogue Manager

Spoken dialogue systems promise efficient and natural access to a large variety of information sources and services from any phone. However, current spoken dialogue systems are deficient in their strategies for preventing, identifying and repairing problems that arise in the conversation. This paper reports results on automatically training a Problematic Dialogue Predictor to predict problematic human-computer dialogues using a corpus of 4692 dialogues collected with the 'How May I Help You' (SM) spoken dialogue system. The Problematic Dialogue Predictor can be immediately applied to the system's decision of whether to transfer the call to a human customer care agent, or be used as a cue to the system's dialogue manager to modify its behavior to repair problems, and even perhaps, to prevent them. We show that a Problematic Dialogue Predictor using automatically-obtainable features from the first two exchanges in the dialogue can predict problematic dialogues 13.2% more accurately than the baseline.

A formal definition of Big Data based on its essential features

2016 ◽  
Vol 65 (3) ◽  
pp. 122-135 ◽  
Author(s):  
Andrea De Mauro ◽  
Marco Greco ◽  
Michele Grimaldi
Keyword(s):  
Big Data ◽  
High Volume ◽  
Formal Definition ◽  
Content Type ◽  
Library Management ◽  
Research Areas ◽  
Current State ◽  
Definition Of ◽  
Practical Implications ◽  
Specific Technology

Purpose – The purpose of this paper is to identify and describe the most prominent research areas connected with “Big Data” and propose a thorough definition of the term. Design/methodology/approach – The authors have analysed a conspicuous corpus of industry and academia articles linked with Big Data to find commonalities among the topics they treated. The authors have also compiled a survey of existing definitions with a view of generating a more solid one that encompasses most of the work happening in the field. Findings – The main themes of Big Data are: information, technology, methods and impact. The authors propose a new definition for the term that reads as follows: “Big Data is the Information asset characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value.” Practical implications – The formal definition that is proposed can enable a more coherent development of the concept of Big Data, as it solely relies on the essential strands of current state-of-the-art and is coherent with the most popular definitions currently used. Originality/value – This is among the first structured attempts of building a convincing definition of Big Data. It also contains an original exploration of the topic in connection with library management.

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