Computer assisted generation and transformation of web content

计算机辅助网页内容的生成和转换

• 批准号: 477757-2015
• 负责人: Makrehchi, Masoud
• 金额: $ 1.75万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=579059
• 关键词: Computer; assisted; generation; transformation; web

The Web has become the underlying fabric for information dissemination in the modern society. Over the years, we observe two emerging trends: First is that the Web is still mainly for human audience. Much of development of the Web technology focuses on the improvement of content consumption by human readers. In the second trend we witness that there is an increasing amount of content on the Web which are machine generated. To improve the ease of consumption of the machine generated data, the final Web content takes on the form of text based articles, graphical visualization and charts, and tabulation of aggregates. This proposal focuses on algorithms and methods that can assist with the generation of Web content for the audience from structured data sets. In particular, we are interested at content transformation techniques such that the end content is tailored some specific audience. Currently, the standard publishing method requires an analyst to summarize the data set, and manually publish the analysis result in a mixture of text, graphs and tables. Due to the manual intensive involvement of the author, in most cases, only one version of the final publication is generated. This limits the readability and accessibility of the underlying information in several ways. The industry partner (Search Engine People) can benefit from the proposed research by the following improvement in their services: (i) their site content will be targeted to individual users. This leads to higher conversion rate and retention of web traffic; (ii) the visibility of the web content will be improved with more referencing from external sites lead to higher traffic and better Google PageRank; and (iii) better selling point to the company's core business and services.

在现代社会，网络已经成为信息传播的基础结构。多年来，我们观察到了两个新的趋势：第一，网络仍然主要面向人类受众。Web技术的发展很大程度上着眼于改善人类读者对内容的消费。在第二个趋势中，我们看到Web上越来越多的内容是由机器生成的。为了提高机器生成的数据的易用性，最终的Web内容采用基于文本的文章、图形可视化和图表以及聚合的表格的形式。 该提案侧重于可以帮助从结构化数据集生成面向受众的Web内容的算法和方法。特别是，我们对内容转换技术感兴趣，以便最终内容针对特定的受众量身定做。 目前，标准的发布方法需要分析师汇总数据集，并以文本、图表和表格的混合形式手动发布分析结果。由于作者的大量手工参与，在大多数情况下，只生成最终出版物的一个版本。这从几个方面限制了底层信息的可读性和可访问性。 行业合作伙伴(搜索引擎人员)可以从拟议的研究中受益，因为他们的服务有以下改进：(I)他们的网站内容将针对个人用户。这将导致更高的转化率和网络流量的保持；(Ii)网络内容的可见性将得到改善，因为更多来自外部网站的引用会带来更高的流量和更好的Google PageRank；以及(Iii)更好地针对公司的核心业务和服务进行销售。