Package dragon.ir.index

A package for doucument indexing and indexing result read.

See:
Description

Interface Summary

Indexer	Interface of document indexing agent
IndexReader	Interface of index reader
IndexWriter	Interface of index writer
IRDocIndexList	Interface of IRDoc Index List
IRRelationIndexList	Interface of IRRelation Index List
IRSignature	Interface of IRSignature
IRSignatureIndexList	Interface of IRSignature Index List
IRTermIndexList	Interface of IRTerm Index List

Class Summary

AbstractIndexer	AbstractIndexer implements basic functions of interface Indexer such as building index for an article and options for section index and relation index
AbstractIndexReader	AbstractIndexReader implements functions defined in interface IndexReader such as getting termdoc and docterm matrix, getting termkey and dockey, getting termindex and docindex, getting all the indexed terms for a given document, getting all the indexed documents for a given term ...
AbstractIndexWriteController	AbstractIndexWriteController implements basics functions including generating IRTermList, IRRelationList for the useage of later processing.
AbstractIndexWriter	The class implements two methods writing termdoc and docterm matrix to disk with options of term based, relation based or both
BasicIndexer	BasicIndexer, providing all basic functions for indexing, can be used to index documents directly
BasicIndexReader	BasicIndexReader is used to read all the indexing information into memory for a indexed collection
BasicIndexWriteController	This class implements function of writing section index.
BasicIndexWriter	The class is used to initialize and write index to disk
BasicIRDocIndexList	The class is used to write or load the indexing information for a given document or document set
BasicIRRelationIndexList	The class is used to write or load the relation indexing information for a given IR relation or relation set
BasicIRTermIndexList	The class is used to write or load the relation indexing information for a given IR term or term set
DualIndexer	The class handles two dimensional document language model indexing
FileIndex	The class is used to read according files storing indexing information.
IndexConverter	Import (export) indexing from (to) text format
IRCollection	IRCollection is the data structure for a document collection
IRDoc	IRDoc is data structure for IR document indexing which can be sorted and thus compared by weight and index
IRRelation	IRRelation is the basic data structure for binary relation extracted from document which can be sorted and compared by index and frequency.
IRSection	IRCollection is the data structure for document section indexing
IRTerm	This is basic indexing unit which can be sorted and compared by index and frequency
OnlineIndexer	The class is designed for indexing in computer memory especially for small document set when writing to disk is not necessary.
OnlineIndexReader	The class is used to read indexing information from memory
OnlineIndexWriteController	The class is the same as BasicIndexWriteController except that it does not store information to disk
OnlineIndexWriter	The class is the same as BasicIndexWriter except that it does not store information to disk.
OnlineIRDocIndexList	The class is used to add or get a given IRDoc
OnlineIRRelationIndexList	The class is used to add or get a given IR relation
OnlineIRTermIndexList	The class is used to add or get a given IR term
TransposeIRMatrix	The class is used to transpose a given IR indexing matrix such as termdoc to docterm

Package dragon.ir.index Description

A package for doucument indexing and indexing result read.

Package Specification

There are two important interfaces. One is indexer which index articles in a corpus. The other is index reader which read out indexing results. The dragon toolkit supports two modes of indexing. The first mode saves the indexing results into disk-based files and ususally fit for large collections. The second mode keeps all information in the memory. The second mode is very conveient and fast, but for small collections only, e.g. collections for text summarization.