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Project Overview
Information Retrieval is the way of finding documents within a collection relevant to a specific query and also detecting which are more relevant than the others. An Information Retrieval System includes indexing, searching and recalling data particularly text from files/documents. The project given to us aims to implement the above using the Inverted Index model. The search engine thus developed should be able to build an index from specified files, and search them based on a user input query.
Approach
The Information Retrieval Engine is supposed to read in from text files, and build an index for each word and create a corresponding posting list for the same. In such a case, it is easier to use Tree Data Structure as it will allow you input words in a specified order, and will contain a pointer to another Link List Data Structure which will store the posting list.Purchase your paper on Design Docutment for Information Retreival Engine
While parsing (which is the building of index), the text file will be read and another temporary file created for each document without the tags. For creating the temporary file tokens will be defined corresponding to each tags present in the original files. Based on the tokens, we will know whether the text is the DocID, Title or Plain Text. This way, the temporary files will have no tags, but we can still identify the various elements of the text. The process is knows as Tokenization. The temporary file will store the DocID, Title, and the text present in the document. Then, the temporary file will be read in word by word, and stored in the tree taking care of stopwords and removing repetitions. The tree is this case will contain two variables for each node
I. Word i.e. each word present in the text file.
II. Link List which will contain the posting list.
In the posting list, which is a Link List Structure, each node will contain three variables
I. DocID which is the document identification
II. Document’s Title to
III. Frequency of the word in the document, for repeated words in a document the frequency will be increased for the document.
After the building of the index, comes the searching/querying part, wherein a query will be taken from the user and the index searched for documents containing those words. The document’s ID and tiles will be output from the most relevant to the least relevant. The query, taken from the user will be stored in another Tree Data Structure. For each word present in the query, the corresponding posting list will be copied to the Query Tree Nodes. In this scenario, the Tree Data Structure definition will be same as above.
To calculate the relevance of each searched document, another link list is created which contains the DocID and the Score. The idf is then calculated, which goes as log (total number of documents/size of link list for each word). After that, the idf is multiplied with the frequency of each word (referred to as tf) to get the score. The score is put in the link list, replacing the frequency present there.
In order to get final relevance, the score is calculated for each document in the second link list. This is done by adding the scores for the words present in query from the original link list, and storing them in the second list for each document. After calculating the scores, and finding the relevance, the corresponding titles for the present DocID’s are printed out.
Stopword removal
The stopwords will be read in from a file, and another tree created for them which will only contain the words (no other variables). Each time while inputting the word in Index Tree Data Structure, the word will be compared with the stopwords, and if any match happens, it will be removed and not built into the index.
Static Index
The user will be given the option to specify a file to store the whole built index for retrieval in the later stage. The index will be saved, in the specified file name, with each word pointing to the corresponding posting list. This will be helpful, so then while loading the index, the insertion of elements in the Index Tree and Posting List Node, will be directly done by reading in the word, and corresponding list.
Architecture
Tree-Link List
Temporary Text File
Classes Used
• Index Tree for the tree data structure
• Posting List for the link list data structure
• Parsing building the index from text files
• Query searching the documents based on a input query
• Stopword while building index and querying to remove common words
• Static Index - Allow to save/load already build index
Class Specifications
1. Index Tree
Components
• Data Structure with string and Link List
1) String to store the words from the text file
) Link List to store the posting list
Methods
• Index Tree constructor
• Index Tree destructor
• InsertStruct
• Retrieve
• Clear
• Empty
• Full
1) Constructor
Requirements None
Purpose Initialize the data members
) Destructor
Requirements None
Purpose De-initialize the data members
) InsertStruct
Requirements Tree is not full
Input New element to be assigned
Purpose Create Tree node, in proper order
4) Retrieve
Requirements None
Input Element to be searched for in the tree
Purpose Searches for the specified element, returns 1 if the element is found otherwise returns 0.
5) Clear
Requirements None
Input None
Purpose Clears the whole tree, deleting all the nodes.
6) Empty
Requirements None
Input None
Purpose Returns 1 if the tree is empty otherwise returns 0.
7) Full
Requirements None
Input None
Purpose Returns 1 if the tree is full otherwise returns 0.
. Posting List
Components
• Data Structure with DocID, Title and Frequency
1) DocID to store the document ID for each word
) Title to store the corresponding document title for the DocID
) Frequency to store number of times the word appears in the document
Methods
• Posting List constructor
• Posting List destructor
• InsertPosting
• Replace
• GetElement
• Clear
• Empty
• Full
• Size
1) Constructor
Requirements None
Purpose Initialize the data members
) Destructor
Requirements None
Purpose De-initialize the data members
) InsertStruct
Requirements List in not full
Input New element to be assigned
Purpose Create new node in Link List, to enter the information there
4) Replace
Requirements None
Input Element to be replaced with
Purpose Replaces the frequency with the score in the present node (related to the DocID).
5) Clear
Requirements None
Input None
Purpose Clears the whole Link List, deleting all the nodes
6) GetElement
Requirements List not Empty
Input None
Purpose Returns the elements present at the cursor
7) Empty
Requirements None
Input None
Purpose Returns 1 if the List is empty otherwise returns 0.
8) Full
Requirements None
Input None
Purpose Returns 1 if the List is full otherwise returns 0.
) Size
Requirements None
Input None
Purpose Returns size of the link list
. Parsing
Components
• DocID, Title, word, nodocs.
1) DocID to store the document ID while reading from file
) Title to store the corresponding document title for the DocID
) Word to store each word you read in from the file
4) Nodocs to store the total number of documents present.
Methods
• Parsing constructor
• Parsing destructor
• Fileread
• Filewrite
• Indexbuild
1) Constructor
Requirements None
Purpose Initialize the data members
) Destructor
Requirements None
Purpose De-initialize the data members
) Fileread
Requirements None
Input Filename of the file to be opened for reading
Purpose TO read from a file document by document i.e. for each document, and store the values of DocID, Tile and text
4) Filewrite
Requirements None
Input DocID, Title, word
Purpose Creates a temporary text file with DocID, Title and Text in it but without the tags present in original documents and creates so for each individual document id
5) Indexbuild
Requirements None
Input word, DocID, Title
Purpose Creates the Tree, with the word inside it and the posting list which will contain the DocID, Title and Frequency.
4. Querying
Components
• Queryword, ScoreList, QueryTree, idf.
1) Queryword to store in the user input query
) ScoreList to create a Link list with DocID, Score in it
) QueryTree to store each word in the query as a separate tree node
4) Idf to store the log (total number of docs/size of link list)
Methods
• Querying constructor
• Querying destructor
• Getinput
• QueryInsert
• Compare
• Calculatelog
• Updatescore
• Sendoutput
1) Constructor
Requirements None
Purpose Initialize the data members
) Destructor
Requirements None
Purpose De-initialize the data members
) Getinput
Requirements None
Input None
Purpose To get the string word this will be the query to search for from the user.
4) QueryInsert
Requirements None
Input Queryword
Purpose Create a tree, with each word in the query in a different node.
5) Compare
Requirements None
Input Index Tree
Purpose Compares both trees, and copies the posting list to the QueryTree from the Index Tree, for the query words.
6) Calculatelog
Requirements None
Input None
Purpose Calculates the idf for each word and multiplies it with the frequency and replaces frequency with the result.
7) Updatescore
Requirements None
Input None
Purpose Updates the score in the ScoreList, by adding the tf x idf for each document present in the QueryTree.
8) Sendoutput
Requirements None
Input None
Purpose Output the document titles, based on the scores from QueryTree.
5. Stopword
Components
• Word, StopWordTree, wordfilename
1.) Word to store in each stopword you read from a specified file
.) StopWordTree to make the stopwords tree
.) Wordfilename to store in name of the file containing stopwords
Methods
• Stopword constructor
• Stopword destructor
• Readfile
• Wordcompare
1) Constructor
Requirements None
Purpose Initialize the data members
) Destructor
Requirements None
Purpose De-initialize the data members
) Readfile
Requirements None
Input Filename of the file to be opened for reading
Purpose To read the stopwords from a file, and create a tree node for each word read in order.
4) Wordcompare
Requirements None
Input word to be compared for
Purpose Checks to see whether the present word is there in the StopWordTree, returns 1 if present, 0 if not
6. Static Index
Components
• filenameindex
1) filenameindex to store in the filename where the Index is supposed to be saved
Methods
• Static Index constructor
• Static Index destructor
• Save Index
• Load Index
• RetreiveNode
• Retreive
1) Constructor
Requirements None
Purpose Initialize the data members
) Destructor
Requirements None
Purpose De-initialize the data members
) Save Index
Requirements None
Input Filename of the file to be opened for saving
Purpose Saves the built index (tree-link list structure) in the specified file.
4) Load Index
Requirements None
Input Filename to be opened for loading
Purpose Opens the file, and reads in the data to create the index (tree-link list structure).
5) RetreiveNode
Requirements None
Input None
Purpose Retrieves the tree nodes, to be stored in the static index file.
6) Retreive
Requirements None
Input Tree node
Purpose Gets the corresponding link list for the tree node, to be stored in static index file.
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