Engineers often need to look for the right pieces of information by sifting through long engineering documents, It is a very tiring and time-consuming job. To address this issue, researchers are increasingly devoting ...Engineers often need to look for the right pieces of information by sifting through long engineering documents, It is a very tiring and time-consuming job. To address this issue, researchers are increasingly devoting their attention to new ways to help information users, including engineers, to access and retrieve document content. The research reported in this paper explores how to use the key technologies of document decomposition （study of document structure）, document mark-up （with EXtensible Mark- up Language （XML）, HyperText Mark-up Language （HTML）, and Scalable Vector Graphics （SVG））, and a facetted classification mechanism. Document content extraction is implemented via computer programming （with Java）. An Engineering Document Content Management System （EDCMS） developed in this research demonstrates that as information providers we can make document content in a more accessible manner for information users including engineers.The main features of the EDCMS system are： 1） EDCMS is a system that enables users, especially engineers, to access and retrieve information at content rather than document level. In other words, it provides the right pieces of information that answer specific questions so that engineers don＇t need to waste time sifting through the whole document to obtain the required piece of information. 2） Users can use the EDCMS via both the data and metadata of a document to access engineering document content. 3） Users can use the EDCMS to access and retrieve content objects, i.e. text, images and graphics （including engineering drawings） via multiple views and at different granularities based on decomposition schemes. Experiments with the EDCMS have been conducted on semi-structured documents, a textbook of CADCAM, and a set of project posters in the Engineering Design domain. Experimental results show that the system provides information users with a powerful solution to access document content.展开更多
Due to the emerging technology era, today a number of firms share their service/product descriptions. Such a group of information in the textual form has some structured information, which is beneath the unstructured ...Due to the emerging technology era, today a number of firms share their service/product descriptions. Such a group of information in the textual form has some structured information, which is beneath the unstructured text. A new attainment which facilitates the form of a structured metadata by recognizing documents which are likely to have some type and this information is then used for both segregation and search process. The idea of this advent describes some attributes of a text that will match with the query object which acts as identifier both for segregation as well as for storage and retrieval. An adaptive technique is proposed to deal with relevant attributes to annotate a document by satisfying the users querying needs. The solution for annotation-attribute suggestion problem is not based on the probabilistic model or prediction but it is based on the basic keywords that a user can use to query a database to retrieve a document. Experiment results show that Querying value and Content Value approach is much useful in predicting a tag for a document and thus prediction is also based on Querying value and Content value which greatly improves the utility of shared data which is a drawback in the existing system. This approach is different, as we consider only the basic keywords to be matched with the content of a document. When compared with other approaches in the existing system, Clarity is a primary goal as we expect that the annotator may improve the annotations on process. The discovered tags assist on quest of retrieval as an alternative to bookmarking.展开更多
This paper proposes an extractive generic text summarization model that generates summaries by selecting sentences according to their scores. Sentence scores are calculated using their extensive coverage of the main c...This paper proposes an extractive generic text summarization model that generates summaries by selecting sentences according to their scores. Sentence scores are calculated using their extensive coverage of the main content of the text, and summaries are created by extracting the highest scored sentences from the original document. The model formalized as a multiobjective integer programming problem. An advantage of this model is that it can cover the main content of source (s) and provide less redundancy in the generated sum- maries. To extract sentences which form a summary with an extensive coverage of the main content of the text and less redundancy, have been used the similarity of sentences to the original document and the similarity between sentences. Performance evaluation is conducted by comparing summarization outputs with manual summaries of DUC2004 dataset. Experiments showed that the proposed approach outperforms the related methods.展开更多
不同用户对文档和信息的需求程度有差异,因此确定用户服务需求权重需要考虑多个因素,包括用户的兴趣、偏好、历史行为等。这些因素的复杂性使得准确捕捉和量化用户需求权重变得相对困难,文档交互运营难度较大。为此,提出基于用户服务需...不同用户对文档和信息的需求程度有差异,因此确定用户服务需求权重需要考虑多个因素,包括用户的兴趣、偏好、历史行为等。这些因素的复杂性使得准确捕捉和量化用户需求权重变得相对困难,文档交互运营难度较大。为此,提出基于用户服务需求权重计算的文档交互运营优化方法。确定不同文档运营模式重要程度,引入KANO模型分析用户对文档内容运营的基本需求。计算用户对文档内容运营机制的满意度系数和不满意系数,获取不同用户的服务需求权重。使用Lofi is Symphony框架简化文档模板,实现运营过程中的文档更新自动化。设计以用户为中心的全过程运营链路,增强用户与文档之间的交互性,优化文档内容运营机制。实验结果表明,优化后的运营机制更高效地更新文档内容,所推荐的文档内容与用户需求的贴合度高于0.9,实现了以用户为中心的内容运营的优化。展开更多
基金This work was supported by the UK Engineering and Physical Sciences Research Council(EPSRC)(No.GR/R67507/01).
文摘Engineers often need to look for the right pieces of information by sifting through long engineering documents, It is a very tiring and time-consuming job. To address this issue, researchers are increasingly devoting their attention to new ways to help information users, including engineers, to access and retrieve document content. The research reported in this paper explores how to use the key technologies of document decomposition （study of document structure）, document mark-up （with EXtensible Mark- up Language （XML）, HyperText Mark-up Language （HTML）, and Scalable Vector Graphics （SVG））, and a facetted classification mechanism. Document content extraction is implemented via computer programming （with Java）. An Engineering Document Content Management System （EDCMS） developed in this research demonstrates that as information providers we can make document content in a more accessible manner for information users including engineers.The main features of the EDCMS system are： 1） EDCMS is a system that enables users, especially engineers, to access and retrieve information at content rather than document level. In other words, it provides the right pieces of information that answer specific questions so that engineers don＇t need to waste time sifting through the whole document to obtain the required piece of information. 2） Users can use the EDCMS via both the data and metadata of a document to access engineering document content. 3） Users can use the EDCMS to access and retrieve content objects, i.e. text, images and graphics （including engineering drawings） via multiple views and at different granularities based on decomposition schemes. Experiments with the EDCMS have been conducted on semi-structured documents, a textbook of CADCAM, and a set of project posters in the Engineering Design domain. Experimental results show that the system provides information users with a powerful solution to access document content.
文摘Due to the emerging technology era, today a number of firms share their service/product descriptions. Such a group of information in the textual form has some structured information, which is beneath the unstructured text. A new attainment which facilitates the form of a structured metadata by recognizing documents which are likely to have some type and this information is then used for both segregation and search process. The idea of this advent describes some attributes of a text that will match with the query object which acts as identifier both for segregation as well as for storage and retrieval. An adaptive technique is proposed to deal with relevant attributes to annotate a document by satisfying the users querying needs. The solution for annotation-attribute suggestion problem is not based on the probabilistic model or prediction but it is based on the basic keywords that a user can use to query a database to retrieve a document. Experiment results show that Querying value and Content Value approach is much useful in predicting a tag for a document and thus prediction is also based on Querying value and Content value which greatly improves the utility of shared data which is a drawback in the existing system. This approach is different, as we consider only the basic keywords to be matched with the content of a document. When compared with other approaches in the existing system, Clarity is a primary goal as we expect that the annotator may improve the annotations on process. The discovered tags assist on quest of retrieval as an alternative to bookmarking.
文摘This paper proposes an extractive generic text summarization model that generates summaries by selecting sentences according to their scores. Sentence scores are calculated using their extensive coverage of the main content of the text, and summaries are created by extracting the highest scored sentences from the original document. The model formalized as a multiobjective integer programming problem. An advantage of this model is that it can cover the main content of source (s) and provide less redundancy in the generated sum- maries. To extract sentences which form a summary with an extensive coverage of the main content of the text and less redundancy, have been used the similarity of sentences to the original document and the similarity between sentences. Performance evaluation is conducted by comparing summarization outputs with manual summaries of DUC2004 dataset. Experiments showed that the proposed approach outperforms the related methods.
文摘不同用户对文档和信息的需求程度有差异,因此确定用户服务需求权重需要考虑多个因素,包括用户的兴趣、偏好、历史行为等。这些因素的复杂性使得准确捕捉和量化用户需求权重变得相对困难,文档交互运营难度较大。为此,提出基于用户服务需求权重计算的文档交互运营优化方法。确定不同文档运营模式重要程度,引入KANO模型分析用户对文档内容运营的基本需求。计算用户对文档内容运营机制的满意度系数和不满意系数,获取不同用户的服务需求权重。使用Lofi is Symphony框架简化文档模板,实现运营过程中的文档更新自动化。设计以用户为中心的全过程运营链路,增强用户与文档之间的交互性,优化文档内容运营机制。实验结果表明,优化后的运营机制更高效地更新文档内容,所推荐的文档内容与用户需求的贴合度高于0.9,实现了以用户为中心的内容运营的优化。
