J. Data Intell.最新文献_第5页

Blockchains

J. Data Intell. Pub Date : 1900-01-01 DOI: 10.1007/978-3-031-13979-6

Christian Dienbauer, Benedikt Pittl, E. Schikuta

引用次数: 1

Automatic Generation of Product Descriptions Using Deep Learning Methods 使用深度学习方法自动生成产品描述

J. Data Intell. Pub Date : 1900-01-01 DOI: 10.26421/JDI4.1-2-2

Akiyo Nadamoto, Kenji Fukumoto, Risa Takeuchi, Hiroyuki Terada, Masafumi Bato

引用次数: 0

Geographic Entity Retrieval for Finding Places Suitable for Certain Purposes by Using Relevance Graphs on Places and Reviews 利用地点和评论上的关联图，寻找适合某些目的的地点的地理实体检索

J. Data Intell. Pub Date : 1900-01-01 DOI: 10.26421/jdi3.4-1

Yui Maekawa, Yoshiyuki Shoji, M. Dürst

{"title":"Geographic Entity Retrieval for Finding Places Suitable for Certain Purposes by Using Relevance Graphs on Places and Reviews","authors":"Yui Maekawa, Yoshiyuki Shoji, M. Dürst","doi":"10.26421/jdi3.4-1","DOIUrl":"https://doi.org/10.26421/jdi3.4-1","url":null,"abstract":"This paper proposes a method of ranking geographic entities (places) where a purpose, given as a query, can be achieved. Most existing map search engines accept only the name of a place or the type of a place. Thus when searchers want to find a suitable place for ``guitar practice'', they have to input a place type such as ``music studio''. To create such a query, prior knowledge (textit{i.e.}, that a music studio is suitable for playing guitar) is required. Our proposed method uses online review information on places to enable direct place retrieval from a given purpose query. Our method creates a bipartite graph consisting of places and the words that appear in the reviews of these places. The relevance between the given keyword query and a place is calculated by using the Random Walk with Restart algorithm. Additionally, we expand the graph with three hypotheses: 1) places that are suitable for the same purpose are similar to each other, and purposes that can be achieved in the same place are similar to each other, 2) the same purpose can be achieved in places with similar metadata, and 3) purposes which have semantically similar meaning can be achieved in the same places. Through an experiment using real review data taken from Google Maps, the usefulness of the proposed method was demonstrated. In particular, experimental result shows that the expansion by places' metadata is effective for finding more relevant places.","PeriodicalId":232625,"journal":{"name":"J. Data Intell.","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126646404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Methods to Aid Unsupervised Evidence-Based Fact Checking for Online Heath News 改进的方法来帮助无监督的基于证据的事实核查在线健康新闻

J. Data Intell. Pub Date : 1900-01-01 DOI: 10.26421/jdi3.4-5

Pritam Deka, Anna Jurek-Loughrey, P Deepak

{"title":"Improved Methods to Aid Unsupervised Evidence-Based Fact Checking for Online Heath News","authors":"Pritam Deka, Anna Jurek-Loughrey, P Deepak","doi":"10.26421/jdi3.4-5","DOIUrl":"https://doi.org/10.26421/jdi3.4-5","url":null,"abstract":"False information in the domain of online health related articles is of great concern, which has been witnessed abundantly in the current pandemic situation of Covid-19. Recent advancements in the field of Machine Learning and Natural Language Processing can be leveraged to aid people in distinguishing false information from the truth in the domain of online health articles. Whilst there has been substantial progress in this space over the years, research in this area has mainly focused on the sphere of political news. Health fake news is markedly different from fake news in the political context as health information should be evaluated against the most recent and reliable medical resources such as scholarly repositories. However, one of the challenges with such an approach is the retrieval of the pertinent resources. In this work, we formulate two techniques for the retrieval of the most relevant authoritative and reliable medical content from scholarly repositories which can be used to assess veracity of an online health article. The first technique is an unsupervised method of generating queries from claims which are extracted from an online health article. We propose a three-step approach for it and illustrate that our method is able to generate effective queries which can be used for retrieval of information from medical knowledge databases. The second method involves a filtering approach for extracting the most relevant information for the claims. We show how this can be achieved with the help of state of the art transformer models and illustrate it's effectiveness over other methods.","PeriodicalId":232625,"journal":{"name":"J. Data Intell.","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134057542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

An Innovative Framework for Supporting Big Moving Objects Tracking, Analysis and Mining Effectively and Efficiently 一种支持大型运动物体跟踪、分析和挖掘的创新框架

J. Data Intell. Pub Date : 1900-01-01 DOI: 10.26421/JDI4.1-2-3

A. Cuzzocrea, Carmine Gallo, E. Mumolo, K. Lenac

引用次数: 0