c# pdf to image without ghostscript: Change font in pdf fillable form SDK Library service wpf .net web page dnn shawn

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

We have developed a program to read through the regulations and apply the Apache

Jakarta Lucene word stemmer [24]. Word stemming is the process of reducing words

down to their word stems. Reducing words to their stems allows software systems to

better match words that would not otherwise match. For example, using word stemming

we can match “waste” and “wastes”, or “dis

posal” and “dispose”. Information retrieval

systems often use word stemming as part of their document retrieval process. Since we

envision the concepts we are adding will be useful for retrieving documents and

performing similarity analysis, word stemming is an important tool for adding concept

metadata to the regulations. The Lucene PorterStemmer implements the simple and

efficient Porter algorithm [72] to stem words. The Porter algorithm uses a series of

rewrite rules for a word to reduce the word down to its word stem.

The basic procedure in adding concepts into the XML document is as follows. First, both

the words in the regulation text and the concept list of noun phrases are stemmed using

the Porter stemming algorithm. In places where the stemmed regulation text matched the

stemmed concept phrase, the unstemmed form of the concept is then inserted in the XML

regulation to annotate the matching regulation text. The annotation is done by adding an

XML element containing the concept within the regElement for the regulation provision.

An example of XML concept elements added for this purpose is shown in Figure 3.8.

Figure 3.8 Example of concept XML element

Used oil shall not be managed in surface impoundments or waste piles unless the units are subject

to regulation under parts 264 or 265 of this chapter.

</regText>

</regElement>

Change font in pdf fillable form - C# PDF Form Data fill-in Library: auto fill-in PDF form data in C#.net, ASP.NET, MVC, WinForms, WPF

Online C# Tutorial to Automatically Fill in Field Data to PDF

convert word form to pdf with fillable; convert pdf fillable form

Change font in pdf fillable form - VB.NET PDF Form Data fill-in library: auto fill-in PDF form data in vb.net, ASP.NET, MVC, WinForms, WPF

VB.NET PDF Form Data fill-in library: auto fill-in PDF form data in vb.net, ASP.NET, MVC, WinForms, WPF

add attachment to pdf form; pdf fillable forms

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

Tagging regulations with key conceptual phrases enables two important usages. First, if

all the provisions within a regulation are tagged with conceptual phrases, it becomes

possible to identify similar or related regulation provisions that do not explicitly reference

each other. For example, federal regulations generally do not reference state regulations,

yet someone reading a federal environmental regulation might want to compare it with a

California environmental regulation. If the California regulations had a different

structure or were composed of separate regulation components issued by different

governing bodies, comparing the California regulations with the federal regulation will be

a difficult task. If all the relevant regulations are tagged at the provision level with their

key conceptual phrases, reconciling the myriad of regulation content structures and

organizational origins may become a tractable problem. Even though some terminology

differs, in general similar regulation provisions should have a number of overlapping key

conceptual phrases, so that the related federal and California regulation provisions should

be identifiable.

Second, tagging regulations with key conceptual phrases enables a tight integration with

the document repository. The concepts can be considered predefined search terms.

Supplementary documents in the document repository that also share a concept or

multiple concepts with a regulatory provision may be strongly related to that regulation.

Using this idea of predefined search terms means that the XML regulation does not need

to explicitly reference every related document individually. Instead, one only needs to

ensure that the important supplementary documents share concepts with the related

provision. This approach also has the effect that as documents are added to the document

repository they immediately become implicitly “linked” from any regulation with which

they share concepts.

3.4.3 References

A second type of metadata applied to the XML framework addresses the references

embedded in the regulation text. Regulation provisions tend to contain a large number of

C# PDF Field Edit Library: insert, delete, update pdf form field

PDF form creator supports to create fillable PDF form in C# Able to add text field to specified PDF file position in C# Support to change font size in PDF form.

convert pdf fill form; convert pdf fillable form to word

C# PDF Text Box Edit Library: add, delete, update PDF text box in

framework. Able to create a fillable and editable text box to PDF document in C#.NET class. Support to change font color in PDF text box.

convert word doc to fillable pdf form; pdf form fill

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

casual English references to other provisions. The density of cross-referencing is

illustrated in Figure 3.9, which shows a sample regulation provision with all cross-

references circled. These references are cumbersome to look up manually, reducing the

readability of the regulation text itself. Moreover, these natural language references are

difficult for software to make use of; the reference information is not very convenient for

software programs to interpret. If references are explicitly marked throughout the XML

regulations using a standard format, tools making use of reference data can be more

easily constructed.

Tools that can make use of regulation references include regulation viewing systems that

link the references with hyperlinks [66], similarity analysis systems that use references in

their algorithms [17, 52], and regulation analysis systems that investigate the structure of

Figure 3.9 Illustration of the density of cross referencing within 40 CFR

VB.NET Create PDF from Word Library to convert docx, doc to PDF in

Change Word hyperlink to PDF hyperlink and bookmark. VB.NET Demo Code for Converting Word to PDF. Add necessary references: RasterEdge.Imaging.Font.dll.

create a pdf form to fill out and save; create a fillable pdf form online

VB.NET Create PDF from Excel Library to convert xlsx, xls to PDF

Change Excel hyperlink to PDF hyperlink and bookmark. VB.NET Demo Code for Converting Excel to PDF. Add necessary references: RasterEdge.Imaging.Font.dll.

create pdf fillable form; convert an existing form into a fillable pdf

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

the regulations. If regulations are not annotated with references in a standardized format

in advance, natural language reference tracking capabilities would be needed. As the

number and type of regulations increase, extracting the references can be even more

complicated since different regulations will have slightly different referencing styles.

Adding reference data at the time an XML regulation is created reduces the complexity

for the development of other processing systems which need to use the references.

The complexity of regulation references ranges from relatively straightforward to

complex. An example of a straightforward casual English reference is the text “as stated

in 40 CFR section 262.14(a)(2).” An example of a more complex reference is the text

“the requirements in subparts G through I of this part” (where the current part is part

265). This latter example can be converted manually into the following list of complete

references: 40.cfr.265.G, 40.cfr.265.H, and 40.cfr.265.I. However, given the large

volume of federal and state environmental regulations, such manual translation of

references is too time consuming to be practical for existing regulations. The same

problem of dealing with a huge number of natural language references has been faced by

at least one other researcher, Justin Needle, when he was working with JUSTIS, a legal

research data provider

. In an article on the automatic linking of legal citations, Justin

Needle writes [66]:

“The conventional method of creating hypertext links between documents

involves manually editing each document and inserting fixed links at the database

production stage. Unfortunately, there is a major problem. The JUSTIS databases

contain millions of citations which, in order to achieve the required functionality,

need to be converted into millions of corresponding hypertext links. The manual

creation of links on this scale is not really an option since link creation is a

laborious process, requiring the services of skilled, and expensive, editors. Even if

an editor is able to identify and process ten links per hour, which is optimistic,

then the human effort required will be approximately a hundred thousand hours

JUSTIS is available at the web address http://www.justis.com.

C# Create PDF from Word Library to convert docx, doc to PDF in C#.

Change Word hyperlink to PDF hyperlink and bookmark. C#.NET Sample Code: Convert Word to PDF in C#.NET Project. RasterEdge.Imaging.Font.dll.

convert pdf to fillable form online; convert word to fillable pdf form

C# Create PDF from OpenOffice to convert odt, odp files to PDF in

An advanced .NET control to change ODT, ODS, ODP forms to fillable C#.NET Project DLLs: Conversion from OpenOffice to PDF in C#.NET. RasterEdge.Imaging.Font.dll.

convert an existing form into a fillable pdf form; add fillable fields to pdf

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

per million links created. … Clearly, there ought to be a better way of tackling

the problem.”

For the research work presented in this thesis, a parsing system was developed using a

context-free grammar and a semantic representation/interpretation system that is capable

of tagging regulation provisions with the list of references that they contain. The parsing

system consists of two phases. First, a context-free grammar parser scans through the

regulation text, constructing parse trees as shown in Figure 3.10. The original reference

for the parse tree in Figure 3.10 was, “…

Subpart O of part 264 or 265”. Then a

secondary parser converts the parse tree into lists of fully specified references. These

references are inserted into the XML regulation as new child elements of the appropriate

regElement XML element.

Note that the references are not tagged as hyperlinks, which would tie the reference to a

particular source for the referred document. Rather, the reference tags simply provide a

complete specification for what regulation provision is referenced. Where the regulation

is located is not specified so that an XML regulation viewing system may select any

document repository of regulations from which to retrieve the referenced provision.

Examples demonstrating the usage of the XML element for regulation references are

shown in Figure 3.11. The next section discusses the development of the reference parser

in detail.

3.4.3.1 Development of a Reference Parser

3.4.3.1.1 Simple Tabular Parsing

Parsing can be viewed as a search problem of matching a particular grammar and lexicon

to a set of input tokens by constructing all possible parse trees [46]. The grammar

defines a set of categories and how the categories can be manipulated. The lexicon

VB.NET Create PDF from PowerPoint Library to convert pptx, ppt to

Files; Split PDF Document; Remove Password from PDF; Change PDF Permission Settings. VB.NET Demo Code for Converting PowerPoint to PDF. RasterEdge.Imaging.Font.dll

convert word document to pdf fillable form; create a fillable pdf form from a pdf

C# Create PDF from PowerPoint Library to convert pptx, ppt to PDF

Convert multiple pages PowerPoint to fillable and editable PDF documents. C#.NET Demo Code: Convert PowerPoint to PDF in C#.NET RasterEdge.Imaging.Font.dll.

create fillable form pdf online; adding signature to pdf form

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

Figure 3.10 Example parse tree for identifying regulation references

Figure 3.11 Example of a reference XML element

defines to what categories the input tokens belong. The search problem is associated

with manipulating the grammar to find all possible matches with the input tokens. A

simple top-down, left-to-right parser is described in this section.

Suppose we start with a very simple model of English grammar. In this grammar we

might say that all sentences are composed of a noun plus a verb phrase. Verb phrases can

be a verb plus a noun, or simply a single verb. This grammar can be represented as

shown in Figure 3.12. We can then create a small lexicon containing the words “cars”,

REF

ASSUME_LEV0

LEV2’

SUBPART UL’

BACKREFKEY

LEV1r’

LEV1p

LEV1r

CONN’ LEV1a’

LEV1a

LEV1s

INT

CONN

PART INT CONL2

Subpart

part

265

264

40.cfr

Used oil shall not be managed in surface impoundments or waste piles unless the units are subject to

regulation under parts 264 or 265 of this chapter.

</regText>

</regElement>

C# Create PDF from Excel Library to convert xlsx, xls to PDF in C#

Create fillable and editable PDF documents from Excel in both .NET WinForms C# Demo Code: Convert Excel to PDF in Visual C# .NET RasterEdge.Imaging.Font.dll.

add attachment to pdf form; create fill pdf form

C# Create PDF Library SDK to convert PDF from other file formats

Create fillable PDF document with fields. Load PDF from existing documents and image in SQL server. RasterEdge.Imaging.Font.dll. RasterEdge.XDoc.PDF.dll.

convert word to pdf fillable form; change font size in pdf fillable form

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

“oil”, and “use”, in which we define what categories these words may match. This

simple lexicon is shown in Figure 3.13.

We can use the simple grammar and lexicon to parse the sentence “cars use oil”. We can

model the parsing process with a category stack, an input stack, and a set of operations

for manipulating these stacks. We start the parsing by adding the “S”, or a sentence start

symbol, to the category stack and the input tokens to the input stack. We can then use

two operations to parse the input. The expand operation is used to expand the top

category on the category stack using one of the grammar rules in Figure 3.12. The match

operation is used to match the top category in the category stack with the top token in the

input stack according to the lexicon rules in Figure 3.13. A parse is considered

successful when both the category stack and the input stack are empty. Table 3.1 shows

the successful parsing of the sentence “cars use oil”, and Figure 3.14 shows the

corresponding parse tree.

In this simple tabular parsing strategy, it is necessary to try all possible expansions of the

grammar categories. For example, the “VP” category in Table 3.1 could also have been

expanded to be a “V”. Since this expansion would not have resulted in a successful parse

the expansion was not used in the example in Table 3.1. When a program is searching

for a parse for an input stack, it will not know in advance which expansions will result in

a successful parse. Therefore it must perform all possible expansions. The general

procedure used, however, is the same as that illustrated in Table 3.1. It is possible to

have multiple parses for a single set of input tokens. It should also be noted that the

lexicon may map the same input token to multiple categories. The parser design

described here is known as left-recursive, and if a grammar rule is left recursive the

parsing algorithm will not terminate [46]. This is because a rule like “VP

VP N” can

be expanded an infinite number of times. In our work, left recursive grammar rules are

not permitted.

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

Table 3.1 Simple parsing example

Category Stack

Input Stack

Operation

Cars use oil

Start

N VP

Cars use oil

Expand

use oil

Match

V N

use oil

Expand

Oil

Match

Finish

Figure 3.12 Simple grammar

Figure 3.13 Simple lexicon

cars

use

oil

Figure 3.14 Simple parse tree

N VP

V N

cars

oil

use

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

3.4.3.1.2 Constructing a Reference Parse Tree

As mentioned above, the reference parsing system is based on a simple tabular parser.

This simple tabular parser must be adapted to the reference identification problem. The

simple tabular parser knows the start and end of the sentence in advance, and

incorporates this information into the algorithm. The reference identification problem is

different from general sentence parsing in that the start and end of the reference are not

known in advance. The termination conditions for the reference parser are changed so

that the parse is considered complete if the category stack is empty. In other words, the

input stack does not need to be empty for the parse to be complete. The parser was also

modified to recognize a number of special category tokens in addition to the lexicon.

These special categories, which can be used in addition to a vocabulary specified in the

lexicon, are shown in Table 3.2. In addition, grammar specifications can use special

categories such as “txt(abc)” to match “abc” input, which makes some patterns more

transparent by bypassing the lexicon.

A third type of grammar category was of the form “ASSUME_LEV1”, where LEV1

represents the level within the reference hierarchy. When the parser produces a category

that starts with “ASSUME_” during a parse, it matches the assumed reference level

(whatever follows the underscore after ASSUME, in this case “LEV1”) with the

identifier for that level within the XML tree

. This is useful when a natural language

reference does not fully denote the reference. For example, in Figure 3.10 the category

“ASSUME_LEV0” was automatica lly assumed to be “40.cfr”, because the reference “…

Subpart O of part 264 or 265” did not exp licitly state that parts 264 and 265 are in 40

CFR.

A WordQueue object is used to tokenize and buffer the input. Regulation provisions are

read individually and added into the WordQueue. The tokenized regulation provision is

This is similar to the standard treatment of “empty” rules, except an assumed value is matched.

CHAPTER 3. XML REPRESENTATION OF REGULATIONS

Table 3.2 Special reference parsing grammar categories

c# pdf to image without ghostscript : Change font in pdf fillable form SDK Library service wpf .net web page dnn shawn_thesis9-part651