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Dynamic Element Retrieval - Computer and Information Science - Lecture Slides, Slides of Applications of Computer Sciences

These lecture slides of the computer and the information sciences are very useful. The important points in these slides are:Dynamic Element Retrieval, Structured Environment, Retrieval of Elements, Vector Space Model, Flexible Retrieval, Document Indexing, Term Weighting, Similarity Coefficients, Lnu-Ltu Term Weighting, Ranking of Elements

Typology: Slides

2012/2013

Uploaded on 04/24/2013

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Dynamic Element Retrieval in a
Structured Environment
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Download Dynamic Element Retrieval - Computer and Information Science - Lecture Slides and more Slides Applications of Computer Sciences in PDF only on Docsity!

Dynamic Element Retrieval in a

Structured Environment

Key Problems

  • Retrieval of elements at desired level of granularity
  • Assigning a rank order to each element that reflects its perceived relevance to the query

Vector Space Model

  • Document Indexing
  • Term Weighting
  • Similarity Coefficients

INEX- Initiative for the Evaluation of

XML Retrieval

  • INEX provides an environment for experiments in structured retrieval
  • Traditionally contains two types of topics CO and CAS
  • Both INEX 2004 and 2005 utilize an evaluation measure known as inex-eval
  • Recall (the proportion of relevant information retrieved) and Precision (the proportion of retrieved items that are relevant

A Method for Flexible Retrieval

  • Input to Flexible Retrieval
  • Construction of the Document Tree
  • Ranking of Elements
  • Output of Flexible Retrieval

Input to Flexible Retrieval

  • Preorder traversal
  • Ranked terminal leaf nodes(paragraphs)
  • Generate document tree(schema and paragraphs)

Construction of the Document Tree

  • Schema determine document tree
  • Calculate Lnu-ltu term weights

Ranking of Elements

  • Address ranking issue’s with Lnu-ltu term weighting
  • Length and normalization issue’s
  • Pivot and slope

Lnu(weight of element vector

formula)

(1 + log( term frequency )) ÷ (1 + log( average term frequency ))



(1 − slope ) + slope × (( number unique terms ) ÷ pivot )

Ltu(weighting of query terms

formula)

(1 + log( term frequency ) × log( N ÷ nk )



(1 − slope ) + slope × (( number unique terms ) ÷ pivot )

Overview of flexible retrieval(cont)

  1. For each document containing a retrieved leaf node a. Get its document schema b. Generate vector representations for inner nodes (elements)
  2. For each term in the query a. Get its inverted file entry and corresponding xpaths

Output of Flexible Retrieval

  • Equivalent to all-element index

Factors of interest

  • Slope and pivot during Lnu-ltu term weighting
  • The n(number of paragraph)

Experiments and Results

  • Attendant file size(dictionary, inverted index, element vectors reduced by 60%, 50% and 50% respectively)
  • 30%- 40% less storage than all-element index
  • Is dynamic element retrieval Cost Effective?