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Open Access
Article
Publication date: 17 July 2020

Mukesh Kumar and Palak Rehan

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are…

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Abstract

Social media networks like Twitter, Facebook, WhatsApp etc. are most commonly used medium for sharing news, opinions and to stay in touch with peers. Messages on twitter are limited to 140 characters. This led users to create their own novel syntax in tweets to express more in lesser words. Free writing style, use of URLs, markup syntax, inappropriate punctuations, ungrammatical structures, abbreviations etc. makes it harder to mine useful information from them. For each tweet, we can get an explicit time stamp, the name of the user, the social network the user belongs to, or even the GPS coordinates if the tweet is created with a GPS-enabled mobile device. With these features, Twitter is, in nature, a good resource for detecting and analyzing the real time events happening around the world. By using the speed and coverage of Twitter, we can detect events, a sequence of important keywords being talked, in a timely manner which can be used in different applications like natural calamity relief support, earthquake relief support, product launches, suspicious activity detection etc. The keyword detection process from Twitter can be seen as a two step process: detection of keyword in the raw text form (words as posted by the users) and keyword normalization process (reforming the users’ unstructured words in the complete meaningful English language words). In this paper a keyword detection technique based upon the graph, spanning tree and Page Rank algorithm is proposed. A text normalization technique based upon hybrid approach using Levenshtein distance, demetaphone algorithm and dictionary mapping is proposed to work upon the unstructured keywords as produced by the proposed keyword detector. The proposed normalization technique is validated using the standard lexnorm 1.2 dataset. The proposed system is used to detect the keywords from Twiter text being posted at real time. The detected and normalized keywords are further validated from the search engine results at later time for detection of events.

Details

Applied Computing and Informatics, vol. 17 no. 2
Type: Research Article
ISSN: 2634-1964

Keywords

Article
Publication date: 23 October 2009

Ching‐Chieh Kiu and Chien‐Sing Lee

The purpose of this paper is to present an automated ontology mapping and merging algorithm, namely OntoDNA, which employs data mining techniques (FCA, SOM, K‐means) to resolve

Abstract

Purpose

The purpose of this paper is to present an automated ontology mapping and merging algorithm, namely OntoDNA, which employs data mining techniques (FCA, SOM, K‐means) to resolve ontological heterogeneities among distributed data sources in organizational memory and subsequently generate a merged ontology to facilitate resource retrieval from distributed resources for organizational decision making.

Design/methodology/approach

The OntoDNA employs unsupervised data mining techniques (FCA, SOM, K‐means) to resolve ontological heterogeneities to integrate distributed data sources in organizational memory. Unsupervised methods are needed as an alternative in the absence of prior knowledge for managing this knowledge. Given two ontologies that are to be merged as the input, the ontologies' conceptual pattern is discovered using FCA. Then, string normalizations are applied to transform their attributes in the formal context prior to lexical similarity mapping. Mapping rules are applied to reconcile the attributes. Subsequently, SOM and K‐means are applied for semantic similarity mapping based on the conceptual pattern discovered in the formal context to reduce the problem size of the SOM clusters as validated by the Davies‐Bouldin index. The mapping rules are then applied to discover semantic similarity between ontological concepts in the clusters and the ontological concepts of the target ontology are updated to the source ontology based on the merging rules. Merged ontology in a concept lattice is formed.

Findings

In experimental comparisons between PROMPT and OntoDNA ontology mapping and merging tool based on precision, recall and f‐measure, average mapping results for OntoDNA is 95.97 percent compared to PROMPT's 67.24 percent. In terms of recall, OntoDNA outperforms PROMPT on all the paired ontology except for one paired ontology. For the merging of one paired ontology, PROMPT fails to identify the mapping elements. OntoDNA significantly outperforms PROMPT due to the utilization of FCA in the OntoDNA to capture attributes and the inherent structural relationships among concepts. Better performance in OntoDNA is due to the following reasons. First, semantic problems such as synonymy and polysemy are resolved prior to contextual clustering. Second, unsupervised data mining techniques (SOM and K‐means) have reduced problem size. Third, string matching performs better than PROMPT's linguistic‐similarity matching in addressing semantic heterogeneity, in context it also contributes to the OntoDNA results. String matching resolves concept names based on similarity between concept names in each cluster for ontology mapping. Linguistic‐similarity matching resolves concept names based on concept‐representation structure and relations between concepts for ontology mapping.

Originality/value

The OntoDNA automates ontology mapping and merging without the need of any prior knowledge to generate a merged ontology. String matching is shown to perform better than linguistic‐similarity matching in resolving concept names. The OntoDNA will be valuable for organizations interested in merging ontologies from distributed or different organizational memories. For example, an organization might want to merge their organization‐specific ontologies with community standard ontologies.

Details

VINE, vol. 39 no. 4
Type: Research Article
ISSN: 0305-5728

Keywords

Article
Publication date: 15 February 2008

H. Mora‐Mora, M. Lloret‐Climent and F. Vives‐Macia

This paper attempts to compare two biological successions, in general any two successions, analysing the differences between them.

177

Abstract

Purpose

This paper attempts to compare two biological successions, in general any two successions, analysing the differences between them.

Design/methodology/approach

An algorithm was designed based on a metric which enables one to calculate the associated distance between two successions and, based on the distance obtained, the type of mutations which have occurred was approached.

Findings

The empirical analysis shows that the transformations caused in the successions have been detected by the metric. Today there are numerous enormously powerful programs able to trawl entire databases and therefore the aim of this paper was not to compare these, but to demonstrate a different way of comparing two given successions.

Practical implications

The paper presents a comparison of two DNA successions having a measure of the degree of similarity between them and their possible mutations.

Originality/value

The metric presented is a generalisation of the Hamming distance in strings of different lengths. The software associated with the metric has made it possible to validate the results obtained.

Details

Kybernetes, vol. 37 no. 1
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 9 December 2022

Qianqun Ma, Jianan Zhou and Qi Wang

Using China’s key audit matters (KAMs) data, this study aims to examine whether negative press coverage alleviates boilerplate KAMs.

Abstract

Purpose

Using China’s key audit matters (KAMs) data, this study aims to examine whether negative press coverage alleviates boilerplate KAMs.

Design/methodology/approach

This study uses Levenshtein edit distance (LVD) to calculate the horizontal boilerplate of KAMs and investigates how boilerplate changes under different levels of the perceived legal risk.

Findings

The findings indicate that auditors of firms exposed to substantial negative press coverage will reduce the boilerplate of KAMs. This association is more significant for auditing firms with lower market share and client firms with higher financial distress. Additionally, the authors find that negative press coverage is more likely to alleviate the boilerplate disclosure of KAMs related to managers’ subjective estimation and material transactions and events. Furthermore, the association between negative press coverage and boilerplate KAMs varies with the source of negative news.

Originality/value

The findings suggest that upon exposure to negative press coverage, reducing the boilerplate of KAMs has a disclaimer effect for auditors.

Details

Managerial Auditing Journal, vol. 38 no. 4
Type: Research Article
ISSN: 0268-6902

Keywords

Article
Publication date: 18 January 2011

David Nicholas, Ian Rowlands, David Clark and Peter Williams

The purpose of this paper is to report on continuing research undertaken on the way the Google Generation behave on the internet and to compare this with an earlier highly…

5812

Abstract

Purpose

The purpose of this paper is to report on continuing research undertaken on the way the Google Generation behave on the internet and to compare this with an earlier highly publicised study by the paper's authors.

Design/methodology/approach

This research use a televised practical experiment and a remote web global test incorporating search, working memory and multi‐tasking experiments.

Findings

The Google Generation appears to behave very differently from older generations. By their own admission they are less confident about their searching prowess and this is also demonstrated by the fact that they viewed fewer pages, visited fewer domains and undertook fewer searches. Also, tellingly, their search statements were much more the product of cut and paste. The Google Generation also have poorer working memories and are less competent at multi‐tasking, both of which may have implications for researching in an online environment.

Originality/value

The paper introduces of multi‐tasking and cognitive measurement in evaluating and describing information‐seeking behaviour; comparing the web behaviour of young and old; the first time this has been shown on public television.

Details

Aslib Proceedings, vol. 63 no. 1
Type: Research Article
ISSN: 0001-253X

Keywords

Article
Publication date: 3 February 2023

Frendy and Fumiko Takeda

Partners are responsible for allocating audit tasks and facilitating knowledge sharing among team members. This study considers changes in the composition of partners to proxy for…

Abstract

Purpose

Partners are responsible for allocating audit tasks and facilitating knowledge sharing among team members. This study considers changes in the composition of partners to proxy for the continuity of the audit team. This study examines the effect of audit team continuity on audit outcomes (audit quality and report lags), pricing and its determinant (lead partner experience), which have not been thoroughly examined in previous studies.

Design/methodology/approach

This study employs string similarity metrics to measure audit team continuity. The study employs multivariate panel data regression empirical models to estimate a sample of 26,007 firm-years of listed Japanese companies from 2008 to 2019.

Findings

The study reveals that audit team continuity is negatively associated with audit fees, regardless of the auditor’s size. This finding contributes to the existing literature by showing that audit team continuity represents one of the determinant factors of audit fee. For clients of large audit firms, companies with higher (lower) audit team continuity issue audit reports in less (more) time. The experience of lead partners is a strong predictor of audit team continuity, irrespective of audit firm size. Audit quality is not associated with audit team continuity for either large or small audit firms.

Originality/value

This study proposes and examines audit team continuity measures that employ string similarity metrics to quantify changes in the composition of partners in consecutive audit engagements. Audit team continuity expands upon the tenure of individual audit partners, which is commonly used in prior literature as a measure of client–partner relationships.

Details

Journal of Accounting Literature, vol. 45 no. 2
Type: Research Article
ISSN: 0737-4607

Keywords

Article
Publication date: 27 April 2010

María‐Dolores Olvera‐Lobo and Lola García‐Santiago

This study aims to focus on the evaluation of systems for the automatic translation of questions destined to translingual question‐answer (QA) systems. The efficacy of online…

Abstract

Purpose

This study aims to focus on the evaluation of systems for the automatic translation of questions destined to translingual question‐answer (QA) systems. The efficacy of online translators when performing as tools in QA systems is analysed using a collection of documents in the Spanish language.

Design/methodology/approach

Automatic translation is evaluated in terms of the functionality of actual translations produced by three online translators (Google Translator, Promt Translator, and Worldlingo) by means of objective and subjective evaluation measures, and the typology of errors produced was identified. For this purpose, a comparative study of the quality of the translation of factual questions of the CLEF collection of queries was carried out, from German and French to Spanish.

Findings

It was observed that the rates of error for the three systems evaluated here are greater in the translations pertaining to the language pair German‐Spanish. Promt was identified as the most reliable translator of the three (on average) for the two linguistic combinations evaluated. However, for the Spanish‐German pair, a good assessment of the Google online translator was obtained as well. Most errors (46.38 percent) tended to be of a lexical nature, followed by those due to a poor translation of the interrogative particle of the query (31.16 percent).

Originality/value

The evaluation methodology applied focuses above all on the finality of the translation. That is, does the resulting question serve as effective input into a translingual QA system? Thus, instead of searching for “perfection”, the functionality of the question and its capacity to lead one to an adequate response are appraised. The results obtained contribute to the development of improved translingual QA systems.

Details

Journal of Documentation, vol. 66 no. 3
Type: Research Article
ISSN: 0022-0418

Keywords

Article
Publication date: 21 August 2023

Zengxin Kang, Jing Cui and Zhongyi Chu

Accurate segmentation of artificial assembly action is the basis of autonomous industrial assembly robots. This paper aims to study the precise segmentation method of manual…

Abstract

Purpose

Accurate segmentation of artificial assembly action is the basis of autonomous industrial assembly robots. This paper aims to study the precise segmentation method of manual assembly action.

Design/methodology/approach

In this paper, a temporal-spatial-contact features segmentation system (TSCFSS) for manual assembly actions recognition and segmentation is proposed. The system consists of three stages: spatial features extraction, contact force features extraction and action segmentation in the temporal dimension. In the spatial features extraction stage, a vectors assembly graph (VAG) is proposed to precisely describe the motion state of the objects and relative position between objects in an RGB-D video frame. Then graph networks are used to extract the spatial features from the VAG. In the contact features extraction stage, a sliding window is used to cut contact force features between hands and tools/parts corresponding to the video frame. Finally, in the action segmentation stage, the spatial and contact features are concatenated as the input of temporal convolution networks for action recognition and segmentation. The experiments have been conducted on a new manual assembly data set containing RGB-D video and contact force.

Findings

In the experiments, the TSCFSS is used to recognize 11 kinds of assembly actions in demonstrations and outperforms the other comparative action identification methods.

Originality/value

A novel manual assembly actions precisely segmentation system, which fuses temporal features, spatial features and contact force features, has been proposed. The VAG, a symbolic knowledge representation for describing assembly scene state, is proposed, making action segmentation more convenient. A data set with RGB-D video and contact force is specifically tailored for researching manual assembly actions.

Details

Robotic Intelligence and Automation, vol. 43 no. 5
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 8 April 2014

Ming Ren, Qiang Wei, Shuangjie Li and Guoqing Chen

The purpose of this paper is to present an intelligent data-driven framework which provides an effective group-buying aggregation service and thus offers a new opportunity for…

Abstract

Purpose

The purpose of this paper is to present an intelligent data-driven framework which provides an effective group-buying aggregation service and thus offers a new opportunity for personalized services in recommendation and advertisement.

Design/methodology/approach

The work presented in the paper analyzes the aggregated group-buying data and creates a compact view of the data which eliminates the potential redundancy and noise. In doing this, the dependencies are discovered from the data in a reverse engineering way. A noise-tolerant method is appreciated, as noise and exception is inevitable in massive data.

Findings

The paper finds that, through the implementation of the intelligent framework, the aggregator will provide a compact view of the group-buying data to customers. According to the empirical study, a 38 percent average decrease of redundancy and noise in the searching results is achieved through the newly built views and corresponding data.

Originality/value

The paper presents the innovative process of discovering the dependencies and creating views in a data-driven and noise-tolerant way. The proposed intelligent framework improves the aggregation performance and forms the basis of personalized services.

Details

Journal of Enterprise Information Management, vol. 27 no. 3
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 16 January 2017

Chirag Shah, Chathra Hendahewa and Roberto González-Ibáñez

The purpose of this paper is to investigate when and how people working collaboratively could be assisted in a fact-finding task, specifically focusing on team size and its effect…

Abstract

Purpose

The purpose of this paper is to investigate when and how people working collaboratively could be assisted in a fact-finding task, specifically focusing on team size and its effect on the outcomes of such a task. This is a follow-up to a previously published study that examined exploratory search tasks.

Design/methodology/approach

This research investigates the effects of team size on fact-finding tasks using a lab study involving 68 participants – 12 individuals, ten dyads, and 12 triads. The evaluation framework developed in the preceding work is used to compare the findings with respect to the earlier traditional exploratory task (Task 1) and the complex fact-finding task reported here (Task 2), with task type being the only difference.

Findings

The analyses of the user study data show that while adding more people to an exploratory search task could be beneficial in terms of efficiency and effectiveness, such findings do not apply in a complex fact-finding task. Indeed, results showed that the individuals were more efficient and effective doing Task 2 than they were in Task 1. Moreover, they outperformed the dyads and triads in Task 2 with respect to these two measures, which relate to the coverage of useful information and its relation to the expression of information needs. If the total time taken by each team is disregarded, the dyads and triads did better than the individuals in answering the fact-finding questions. But considering the time effect, this performance boost does not keep up with the increased group size.

Originality/value

The findings shed light not only on when, how, and why certain collaborations become successful, but also how team size affects specific aspects of information seeking, including information exposure, information relevancy, information search, and performance. This has implications for system designers, information managers, and educators. The presented work is novel in that it is the first empirical work to show the difference in individual and collaborative work (by dyads and triads) between exploratory and fact-finding tasks.

Details

Aslib Journal of Information Management, vol. 69 no. 1
Type: Research Article
ISSN: 2050-3806

Keywords

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