سند علمی

Automatic Text Summarization Based on the Global Document Annotation

چکیده

The GDA (Glol)al Do(:ument Annotation) t)roject t)roposes a tag set which allows machines to automatically infer the underlying semantic/pragmatic structure of documents. Its objectives are to promote development and spread of N L P / A I at)plications to render GDA-tagged do(:uments versatile and intelligent (:ontents, wld(:h shouhl motiwtte W W W (World Wide Web) users to tag their doemnents a~s l)art of content authoring. This 1)aper discusses automatic text sunnnariz~tion based on GDA. Its mifin features are a domain/style-fi'ee algorithm and personalization on SUlmnarization whi(:h reflects readers' interests and preferences. In order to calculate the iml)ort~m(:e score of a text element, the algorithm uses st)re;uting aetiwttion on an intradoeulnent network whi(:h conm'.(:ts text elements via thematic, rhetorical, and corefere.ntial re.lations. The i)roi)osed method is flexible enough to dynami(:ally gen(,rate sl lnll l laries of wLrious sizes, i Slllll111ary t)rowse.r SUl)porting I)ersonalization is reported ~m well. 1, I n t r o d u c t i o n The W W W hiLs opened up all era in which an unrestricted nunfl)er of people i)ut)lish their messages (dectronically through their online do(:mnents. However, it is still very hard to automatically process (:ontents of those documents. The reasons include the following: 1. HTML (HyperText Markup Language) tags mainly specify the physical layout of documents. They address very fe.w (:on~,ent-related annotations. 2. Hypertext links cannot very nmch 11(;11) readers recognize the content of a document. 3. The W W W authors tend to 1)e less earefifl about wording and readability than in traditional t)rintcd media. Currently there is no systematic means for quality control in the WWW. Although HTML is a fle.xible tool that allows you to freely write and read messages on the WWW, it is neither very c(mvenient to readers nor suital)h: for automatic 1)roeessing of contents. We have been deveh)t)ing an integrated platfornl for (loeunmnt authoring, t)ul)lishing. &lid reltse by combining natural language and W W W teehnoh)gies. As the first ste l) of our project, we ([efined a new tag set and developed tools for editing tagged texts and browsing these texts. The browser has the functionality of summarization an(l (:ont(ult-base(l retrieval of tagged docmnents. This l)aper focuse.s on summarization t)ased on this system. The main features of our summarization method are a dmnain/styh.~-free algorithm and l)ersonalization to reflect readers" interests and preferen(:es. This method mtturally outperfornm the tr~tditional summarization methods, which just pick out senten(:(,.s highly scored on the basis of superii(:iM clues such as word count, and so on. 2 G l o b a l D o c u m e n t A n n o t a t i o n GDA (Global Do(:mne.nt Almotation) is a challenging t)rojeet to Inake W W W texts nl&(:hineundel'standabh~ on the basis of a new tag set. and to develo l) Col~tent-t)ased presentation, retrieval, question-answering, summarization, and translation systems with mu(:h higher quality thorn before. GDA thus t)roposes an integrated global platform for ele(:tronic conl;ent authoring, presentation, and reuse. The GDA tag se.t is based on XML (Extensibh; Markup Language), and designed ~us (:Oml)atible as possible with HTML, TEl. EAGLES, and so forth. An example of a GDA-tagged sentence is as follows: t ime flies like an arrow . means sentential unit. . . . . alld lllealt 11o1111.

اسناد مشابه

  • Automatic Text Summarization using Document Clustering Named Entity Recognition

    مقاله‌ی دسترسی آزاد۲۰۲۲International Journal of Advanced Computer Science and Applications['Senthamizh Selvan. R', 'K. Arutchelvan', '']

    Due to the rapid development of internet technology, social media and popular research article databases have generated many open text information. This large amount textual information leads 'Big Data'. Textual can be recorded repeatedly about an event or topic on different webs

  • Automatic Text Summarization for Annotating Images

    سند علمی۲۰۱۳Gediminas Bertasius

    With an explosion of image data on the web, automatic image annotation has become an important area of machine learning, computer vision and natural language processing research. The goal of automatic image annotation systems is to generate the key words or sentences that capture

  • Automatic Text Summarization of Newswire: Lessons Learned from the Document Understanding Conference

    سند علمی۲۰۰۵AAAIAni Nenkova

    Since 2001, the Document Understanding Conferences have been the forum for researchers in automatic text summarization to compare methods and results on common test sets. Over the years, several types of summarization tasks have been addressed—single document summarization, multi

  • From SweSum to ScandSum- Automatic text summarization for the Scandinavian languages

    سند علمی۲۰۰۳Hercules Dalianis

    In automatic text summarization, the most relevant parts of a document are extracted and put together in a non-redundant summary that is shorter than the original document. A more advanced form of summarization is multi-text summarization where several texts are condensed into on

  • Multi-document Automatic Text Summarization Using Entropy Estimates

    سند علمی۲۰۰۴SOFSEMG. Ravindra, N. Balakrishnan, K. R. Ramakrishnan

    This paper describes a sentence ranking technique using entropy measures, in a multi-document unstructured text summarization application. The method is topic specific and makes use of a simple language independent training framework to calculate entropies of symbol units. The do

  • Resource Lean and Portable Automatic Text Summarization

    سند علمی۲۰۰۷MARTIN HASSEL

    Today, with digitally stored information available in abundance, even for many minor languages, this information must by some means be filtered and extracted in order to avoid drowning in it. Automatic summarization is one such technique, where a computer summarizes a longer text