jiit;project 2013-14,project presentation

AN EFFICIENT APPROACH

FOR ILLUSTRATING WEB DATA OF USER SEARCH

RESULTS

INPUT URL

WRAPPER GENERATIO

N

DATA EXTRACTIO

N

SEARCH ENGINE

EXTRACTOR

SEARCH RESULT RECORD

CONTENT LINE

EXTRACTION

DATA ALIGNMENT

ANNOTATORS

LINE SEPARATOR

BLOCK EXTRACTIO

N

ANNOTATION WRAPPER

ANNOTATED GROUPS

COMBINING ANNOTATOR

S

NEW RESULT PAGE

GOOGLE SEARCH CONTENT LINE

•LINK•TEXT•LINK-TEXT•LINK-HEAD•TEXT-HEAD•LINK-TEXT-HEAD•HR LINE• BLANK LINE

GOOGLE SEARCH BLOCKS

To identify similar blocks we check for block similarity on basis of-

•TYPE distance•SHAPE distance•POSITION distance

Candidate Content Line Separators

•blank line (e.g., the <p> tag) •visual line (e.g. the <HR> tag).

(1) the line following an HR-LINE (2) if there is only one line starting with a number in a block, this line is a first line; (3) if only one line in a block has the smallest position code ,this line is a first line (4) if there is only one BLANK line in a block, the line following the BLANK line is the first line.

Fist line of block

Tag path

•Sibling•child

Tag Tree

Wrapper Integration

Relationships between data unit (U) and text node (T):

•One-to-One Relationship T=U

•One-to-Many Relationship T )U

•Many-to-One RelationshipT (U

•One-To-Nothing RelationshipT!=U

Five common features shared by the data units

•Tag Path (TP)•Data Content (DC)•Data Type (DT)•Adjacency (AD)•Presentation Style (PS)

Alignment Algorithm

Here we will apply our data alignment algorithm to align the semantically same data in a group

After Alignment Algorithm

Same semantic data are aligned in a column as shown in fig.

Output

Annotators

• Table annotator• Query-based annotator• Schema value annotator• Frequency-based annotator• Same-prefix annotator• Common knowledge based annotator:

Let P(L) be the probability that L is correct in identifying a correct label for a group of data units when L is applicable. P(L) is essentially the success rate of L. Specifically, suppose L is applicable to N cases and among these cases M areannotated correctly, then P(L)=M/N

Probability

Labelling

Suitable annotator is applied and then label the data

Annotation Wrapper

attribute= <label; prefix; suffix; separators; unit index>.

•comparing all the suffixes

•compare the prefixes of all the data units

New Result Page

This is a new result page with less no. of result record but all the result data will be annotated and efficient.

Tools

Jsoup is a Java library for working with real-world HTML. It provides a very convenient API for extracting and manipulating data, using the best of DOM, CSS, and jquery-like methods.

•Other Tools:•Webharvest•Htmlunit

[1] H. Zhao, W. Meng, Z. Wu, V. Raghavan, and C. Yu, “FullyAutomatic Wrapper Generation for Search Engines,” Proc. Int’l Conf. World Wide Web (WWW), 2005.

[2] Y. Zhai and B. Liu, “Web Data Extraction Based on Partial Tree Alignment,” Proc. 14th Int’l Conf. World Wide Web (WWW ’05),2005.

[3] Y. Lu, H. He, H. Zhao, W. Meng, and C. Yu, “Annotating Structured Data of the Deep Web,” Proc. IEEE 23rd Int’l Conf. Data Eng. (ICDE), 2007

[4] J. Wang and F.H. Lochovsky, “Data Extraction and Label Assignment for Web Databases,” Proc. 12th Int’l Conf. World Wide Web (WWW), 2003.

[5] Yiyao Lu, Hai He, Hongkun Zhao, Weiyi Meng, “Annotating Search Results from Web Database”, IEEE, 2014

References