Structured text
A Boosting Algorithm for Classification of Semi Structured Text
... using text processing sys- tems, a text can be converted into a semi-structured text annotated with parts-of-speech, base-phrase in- formation or syntactic ...in text, rather than to ...
8
Natural Language Access to Structured Text
... NATURAL LANGUAGE ACCESS TO STRUCTURED TEXT COLING 82, J Horeck~ {eft ) North Holland Publishing Company Cc~ Academt~ 1982 NATURAL LANGUAGE ACCESS TO STRUCTURED TEXT J e r r y R Robbs, Donald E W a l k[.] ...
6
DEFT: A corpus for definition extraction in free and semi structured text
... While variations of the X is a Y form are in- deed common definition sentence structures, they do not capture a wide range of definition struc- tures that appear in both free and semi-structured text. In ...
8
“Expertness” from Structured Text? RECONSIDER: A Diagnostic Prompting Program
... and William Le~zis, "Methodology for Creation of and Access to a Clinical Database," ProceedL-tgs of t/m ~ r s t In~e~,m.,~onal Cm'~J'erence on Medical Co.tputer Science, IEEE Computer S[r] ...
8
Evaluating Discourse in Structured Text Representations
... Sentence order discrimination This model is identical, except for task-specific changes. The goal of this synthetic task, proposed by Barzilay and Lapata (2008), is to capture discourse coher- ence. A negative class is ...
8
A Sequence Modeling Approach for Structured Data Extraction from Unstructured Text
... of structured information from un- structured text has always been a problem of interest for NLP ...community. Structured data is concise to store, search and retrieve; and it facilitates ...
10
Learning to Embed Semantic Correspondence for Natural Language Understanding
... The goal of NLU is to extract meaning from a nat- ural language and infer the user intention. NLU typically involves two tasks: identifying user in- tent and extracting domain-specific entities, the second of which is ...
10
Structured and Logical Representations of Assamese Text for Question Answering System
... as text documents, web pages and books contain information in a language specific syntactic form, not suitable for automatic processing through ...The structured text representation shows the ...
12
THE IMPACT OF INFORMATION SYSTEM SUCCESS ON BUSINESS INTELLIGENCE SYSTEM EFFECTIVENESS
... current text clustering methods do not consider the feature of semi-structured texts (structured, unstructured, semi-structured), there are the high dimensions and high sparseness problems ...
7
Analysis and Implementation of Text Mining for Different Documents
... making structured data from unstructured and semi structured text is called text ...mining. Text mining is defined as bag of ...
5
Neural Text Generation from Structured Data with Application to the Biography Domain
... Concept-to-text generation renders structured records into natural language (Reiter et al., 2000). A typical application is to generate a weather forecast based on a set of structured meteorological ...
11
Structured prediction models for RNN based sequence labeling in clinical text
... Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In the clinical domain one major ap- plication of sequence labeling involves ex- ...
10
Towards a Structured Representation of Generic Concepts and Relations in Large Text Corpora
... Existing work on pre-defined relation extraction have implemented methods of supervised, semi- supervised, bootstrapped and unsupervised classi- fication(Zhao and Grishman, 2005), (Kambhatla, 2004) (Bunescu and Mooney, ...
9
Delivering Value from Resume Repositories TCS WhitePaper Sep2011
... Resumes are typically free-form or semi-structured English documents received in text (.TXT), Microsoft Word (.DOC, .DOCX, .RTF), HTML or PDF formats. Resumes may occasionally contain tables or images. ...
12
Assessing the quality of evidence for verbal autopsy diagnosis of stroke in Vietnam.
... free text in the verbal autopsy questionnaires shows that VA is effective for stroke and VA content analysis can be utilized as an adjunct to conventional validation studies in developing countries where ...
9
FACILITATING DOCUMENT ANNOTATION USING METADATA
... Clustering algorithms are typically used for exploratory data analysis, where there is little or no prior knowledge about the data. This is precisely the case in several applications of Computer Forensics, including the ...
7
PERFORMANCE ANALYSIS OF WLAN UNDER VARIABLE NUMBER OF NODES USING THE ADJUSTABLE PARAMETERS IN EDCA
... The fuzzifier is a process of translating the inputs into feature values. The proposed approach uses a set five features, the fuzzier defines a value in the range 1 to 5 for each features. Based on these fuzzy values, ...
8
PDTB Discourse Parsing as a Tagging Task: The Two Taggers Approach
... unannotated text documents producing the full discourse structure of the text, including both implicit and explicit relations, and so can be realistically used in NLP ...
9
Information Extraction andRule Prediction Using DiscoTEX
... After constructing an IE system that extracts the desired set of slots for a given a sample document, a database is constructed from a corpus of texts by applying the extractor to each document to create a set of ...
7
A Survey on Text Mining Procedures and Exploring Techniques
... of text mining in order to preserve the resources, but accuracy of this cluster approach is susceptible due to initial cluster center selection ...of text categorization is available which are not much ...
6