Of textual data

As described above the primary sources of data for these analyses were fact books. Each fact book contained a number of reports, articles, and analyses prepared by analysts, journalists, or researchers studying the particular firm of interest. In general, the fact books were voluminous and contained twenty to thirty papers focusing on each of the two study periods. Although a few papers were short, most varied between five and ten pages in length. Over 60,000 pages of textual data were analyzed in the course of the study. 

However, the present protocols represent only the first step in the automated extraction and analysis of textual data. In reality, the XML document has provided a method of speeding up the extraction of information from a text source that possesses a particularly high level of structure (i.e. the Treatise). But Treatises are... 

Cooper, D. Dicker, M.E. L)mch, M.F. Sorting of Textual Data Bases a Variety Generation Approach to Distribution Sorting. Inf. Process. Manage, 1980,16, 49-56. 

The internal structure of a full-text database is significantly different from that of other types such as relational (row/column/table-oriented) or object-oriented databases. The domain of a full-text database is the indexing and storage of large amounts of textual data. Indexes based on words occurring in the text corpus, proximity operators to locate phrases and close spatial relationships between words, and probabilistic thesauri to define word, concept, and content clusters are important characteristics of this type of database. See Bibliographic Database Object-oriented Database Object-Relational Database Relational Database and Textual Database. 

A number of file formats exist which serve different purposes in the area of textual data exchange. The simplest of them is of course plain 7-bit ASCII, and also ISO 8859-x text exchange is quite portable. The shortcomings of these text formats are that they neither support stylistic attributes nor content-based markup. 

Fig. 16.3. Screen shots of PGVL Hub. It has two ways to display molecules and their properties (Structural Viewer panel and Table viewer panel). It has been integrated with SpotFire for data visualization. It also has a decision maker capable of handling numerical and textual data as well as user selections by hand.

The development of the Internet and the resulting capability for widespread storage and retrieval of textual and numerical data have made it quite easy to gain access to... 

A verification system can automatically create user dialogs or forms for input of fielded data on the basis of a human-readable textual specification, preferably in XML. This specification contains the following information ... 

An introduction to SQL is provided in Chapter 3, but with an emphasis on examples relevant to chemical information rather than business information, which is often used in other books. Chapter 4 discusses some of the RDBMS that are available, namely Oracle, MySQL, and PostgreSQL. All of them use SQL to insert, delete, update, and select data. Chapter 5 shows ways in which client programs, including Web-based applications, are used to connect to the database server. Chapter 6 examines ways in which RDBMS are typically used to handle numerical and textual chemical information using relational tables. An example of using data files from the PubChem project is included. 

Another major characteristic of front end systems briefly mentioned in the context of query uploading is the ability to perform query translation. In general, each host computer uses its own own command language and, particularly in the field of bibliographic and other textual data bases, a query translator is desirable to ensure that a particular query can be searched against the many and varied relevant files on diverse host computers. In chemical structure systems, the only query translator available to date is TopFrag... 

Causal identification may also be influenced by the data collection methods. Data are usually collected in the form of textual descriptions of the sequence of events of the accident, which, as we have seen, tend to concentrate on obvious conditions or events closely preceding the accident in time and tend to leave out less obvious or indirect events and factors. There is no simple solution to this inherent bias On one hand, report forms that do not specifically ask for nonproximal factors often do not ehdt them while, on the other hand, more directive report forms that do request particular information may limit the categories or conditions considered [101]. 

Current systems require many steps to include graphical objects and other non-textual entities into documents. The new systems will support easy incorporation of multiple data types (e.g., chemical structures, reaction schemes, graphs, charts, data tables, etc.) while retaining the characteristics of the objects. One will be able to manipulate the object in its native mode and append ancillary data to the document if desired. 

Besides the data derived from the schemes, the metafiles (the pure graphic) and, of course, the data from the textual input (title, abstract, bibliographic data) will also be stored in the base file. This will be the source for indexes or subfiles, and for reaction databases for existing retrieval systems. As far as the used retrieval system will allow, all of these data except the display-only graphic metafile may be searchable. 

For Text Mining, a significant amount of pre-processing of the textual data may be required, dependent on the domain and the user s requirements. Some natural language analysis may be used to augment or replace some words by their parts of speech or by their base forms. Post-processing of the results of Text Mining is usually also necessary. 

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