Automatic Discovery of Logical Document Structure
Automatic Discovery of Logical Document Structure
复制标题
自动发现逻辑文档结构
DOI：
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发表时间：
1998
期刊：
影响因子：
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通讯作者：
K. Summers
中科院分区：
文献类型：
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作者：
K. Summers
The availability of large, heterogeneous repositories of electronic documents is increasing rapidly, and the need for flexible, sophisticated document manipulation tools is growing correspondingly. These tools can benefit greatly by exploiting logical structure, a hierarchy of visually observable organizational components of a document, such as paragraphs, lists, sections, etc. Knowledge of this structure can enable a multiplicity of applications, including hierarchical browsing, structural hyperlinking, logical component-based retrieval, and style translation.
Most work on the problem of deriving logical structure from document layout either relies on knowledge of the particular document style or finds a single flat set of text blocks. This thesis describes an implemented approach to discovering a full logical hierarchy in generic text documents, based primarily on layout information. Since the styles of the documents are not known a priori, the precise layout effects of the logical structure are unknown. Nonetheless, typographical capabilities and conventions provide cues that can be used to deduce a logical structure for a generic document. In particular, the key idea is that analyses of the text contours at appropriate levels of granularity offer a rich source of information about document structure.
The problem of logical structure discovery is divided into problems of segmentation, which separates the text into logical pieces, and classification, which labels the pieces with structure types. The segmentation algorithm relies entirely on layout-based cues, and the classification algorithm uses word-based information only when this is demonstrably unavoidable. Thus, this approach is particularly appropriate for scanned-in documents, since it is more robust with respect to OCR errors than a content-oriented approach would be. It is applicable, however, to the problem of analyzing any electronic document whose original formatting style rules remain unknown; thus, it can provide the basis for flexible document manipulation tools in heterogeneous collections.
