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.

网络已成为现代社会信息传播的潜在结构。多年来，我们观察到两个新兴趋势：首先是网络仍然主要是针对人类观众的。 Web技术的大部分开发都集中在人类读者的内容消费方面的改善。在第二个趋势中，我们目睹了机器生成的网络上越来越多的内容。为了提高机器生成数据的消耗性，最终的Web内容采用了基于文本的文章，图形可视化和图表的形式以及汇总的制表。 该建议重点是可以从结构化数据集为受众生成Web内容的算法和方法。特别是，我们对内容转换技术感兴趣，使最终内容量身定制了一些特定的受众。 当前，标准发布方法要求分析师汇总数据集，并手动发布分析结果，以文本，图形和表格的混合。由于作者的手动密集程度，在大多数情况下，只生成了最终出版物的一个版本。这以几种方式限制了基础信息的可读性和可访问性。 行业合作伙伴（搜索引擎人员）可以通过以下服务的改进从拟议的研究中受益：（i）他们的网站内容将针对单个用户。这导致更高的转化率和网络流量的保留； （ii）通过从外部站点进行更多参考会导致流量更高和更好的Google Pagerank，将提高Web内容的可见性； （iii）更好地销售公司的核心业务和服务。