Data collection method: semi- structured observation
Data value storage for compressed semi-structured data
... a method would reduce the number of dictionaries without impacting on the compressed data ...any method of combining dictionaries that causes the token sizes within the compressed data to ...
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A semi-automatic approach for building ontologies from a collection of structured web documents
... well structured and organized in browsable collections, describing the characteristics of entities from a single type, where each page describes one ...or data sheets are often ...
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Automatic ontology learning from semi-structured data
... The gold standard ontology and the learned ontology are going to be aligned in this section. The DMA method is going to be used for alignment. There are also other methods that use only string similarity matching ...
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Collectively Representing Semi Structured Data from the Web
... In semi-supervised transductive learning, a few en- tities of each class are labeled, and learning method extrapolates these labels to a larger number of un- labeled data ...
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Discovery driven analysis on semi-structured text data
... In practice, in order to analyze a set of text documents (i.e. a corpus), an analyst would input a few keywords to describe each dimension she is interested in. Then, the system would structure the corpus around these ...
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Collectively Representing Semi-Structured Data from the Web
... Introduction Semi-structured data extracted from the web (in some cases extended with hyponym data derived from Hearst patterns like “X such as Y”) have been used in several tasks, including ...
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Chapter 12. XML and Internet Databases. Introduction. Structured, Semi Structured and Unstructured Data
... as data elements: This approach would work for storing a collection of documents that follow a specific XML DTD or XML ...leaf-level data elements within the XML ...
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Chapter 29 Keyword Search on Large-Scale Structured, Semi-Structured, and Unstructured Data
... either data- driven methods or usage-driven methods. The data-driven query suggestion methods utilize the data ...apply data mining techniques to identify the correlations among data, ...
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Generalized discrimination discovery on semi-structured data supported by ontology
... in data collection, processing, management and storage ...example, data warehouses store data of banking transactions, sales and purchases, personal health records, etc; genomic databases ...
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Multidimensional Modeling of Semi-Structured Data: XML Documents and Tweets
... Twitter is a system for information sharing; it allows a user to talk about their daily activities, to seek or share information and to track other users who post messages called Tweets. A tweet was originally restricted ...
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Concept-based exploration of rich semi-structured data collections
... a collection of projects on ...GitHub data currently plays in the hiring ...GitHub data in the recruitment process and therefore, developers are often contacted about positions for which they are not ...
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Methods of Data Collection- Observation, Interview & Focus Group Discussion
... Questionnaire Method Questionnaire is the most commonly used method in survey. Questionnaires are a list of questions either an open- ended or close - ended for which the respondent give answers. ...
Database search vs. information retrieval : a novel method for studying natural language querying of semi-structured data
... benchmark data set that is based on a test collection originally used to evaluate information retrieval ...The data set contains 45 information needs developed on the Internet Movie Database (IMDb), ...
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STRUCTURED METHODS: INTERVIEWS, QUESTIONNAIRES AND OBSERVATION
... Self-completion surveys can also be group administered. For example, a researcher may ask a class of school pupils to fill in a question- naire. If a pupil is uncertain about the meaning of a question, he or she can ask ...
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Very Fast Similarity Queries on Semi-Structured Data from the Web
... K-NN+PIC-D method incurs a small amount of pre-processing time ...K-NN+PIC-D method, indicating the speedup of 13x to 240x over K-NN-Baseline and 65x to 150x over ...
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The LHAM Log-Structured History Data Access Method
... case consideration is an issue also for queries with key ranges or time ranges, we concentrate on point queries as they already capture the essence of the problem. Our analytical model could be extended to range queries, ...
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An analysis and Implication of Data Mining Techniques using Semi structured Data towards clinical data sets
... TF-IDF method and framework for text classification is ...sorting semi structured data from web pages and ...fetching data as per the requirements using various SQL ...
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An Analysis and Implication of Data Mining Techniques using Semi structured Data towards clinical data sets
... TF-IDF method and framework for text classification is ...sorting semi structured data from web pages and ...fetching data as per the requirements using various SQL ...
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Comparison of Performance in Text Mining Using Text Categorization of Semi Structured Data
... of data mining, which is widely being used to discover hidden patterns and significant information from the huge amount of unstructured .../ semi structured data cannot simply be used for ...
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