# Presentation: 022394

## Susan Hauser, Jonathan Schlaifer, Tehseen Sabir, Dina Demner-Fushman, George Thoma
Lister Hill National Center for Biomedical Communications
National Library of Medicine
National Institutes of Health
Department of Health and Human Services

**Lister Hill National Center for Biomedical Communications**
**National Library of Medicine**
**National Institutes of Health**
**Department of Health and Human Services**

**Correcting OCR Text by Association with Historical Datasets**

## The MARS System

## Problem: The affiliation field requires a disproportionate amount of time to correct and verify.  

**Poor OCR of italic fonts.**
**Only the first affiliation is kept.**
**OCR server does not recognize diacritics**
**( and OCR text is not double-keyed)**

## Verification operator’s view for 

**Verification operator’s view for **
**correcting OCR of affiliation field**

## Hidaka C  - in PubMed citations, associated with:

## A Feasibility Study found that:

**47% of author names in a test set of 20,000 were found in a database of 324,000 unique author name/affiliation/zip code triples taken from MARS verified data.**
**19% of affiliations in the test set were found in the database when searched for by zip code.**

## Similarity Scoring Algorithm

**Hybrid partial matching algorithm: find chains of words that are within a word-by-word edit distance.**
**Compare OCR affiliation text to affiliations historically associated with the OCR author name(s).**

## Similarity Scoring Algorithm

**Similarity Score = **
**((# words in longest chain of  partially-matched words)**
**+**
**(# words in second-longest chain of  partially-matched words))**
**/**
**(#words in the shorter string)**
** **

## Similarity Scoring Algorithm

**Results using a threshold score of 0.58 **
**on ground truth test set of 519 samples:**
**True positives****	****34%**
**False positives****	****06%     ****<<<<<**
**True negatives****	****44%**
**False negatives****	****16%**

## Steps toward implementationin MARS

**Build a large author/affiliation/zip code table from PubMed citations.**
**Develop a daemon module to find and score candidate affiliations and create new affiliation records.**
**Select a threshold for the Similarity Score.**

## Author/Affiliation/Zip code table

**Program written to automatically fetch PebMed citations in XML format, extract selected data and populate table.**
**704,229 unique author/affiliation/zip code (when present) entries from 2000 through 2002 (so far).**
**394,768 unique author names**
**About 34% of authors have more than one affiliation.**

## Author Names with Multiple Affiliations – Low End

## Daemon module - SeekAffiliation

**Use OCR 1****st**** author to fetch affiliations from Author/Affiliation/Zip Code table.**
**Augment with 2****nd**** and 3****rd**** author affiliations if necessary.**
**Prune with zip code if present.**
**Obtain OCR affiliation field text.**

## Daemon module - SeekAffiliation

**Submit OCR affiliation and  a list of found affiliations to the similarity scoring algorithm.**
**Insert new records linked to the article in question for candidate affiliations with similarity scores greater than the threshold.**

## Similarity Score threshold

**Goal: Keep % of false positives low and still be useful.**
**Test output of SeekAffiliation from 31 journal issues (666 articles) previously processed by MARS.**
**Have 464 articles, 2,366 candidate affiliations for testing.**
**Visually compare candidate affiliations from SeekAffiliation to verified affiliation.**
**Two evaluators (so far).**

## Results of Visual Comparison

## Why we are encouraged: Examples of true positives

**Example 1:**
**OCR Text: **
**aEcotoxicology Research Unit, Chemistry Department, **
**Cork Institute of Technology, Bishopstown, Cork, Ireland**
**blrish Distillers Group Ltd., Bow Street Distillery, Smithfield, Dublin 7, Ireland**
**Found Affiliation:**
**Chemistry Department, **
**Cork Institute of Technology, Bishopstown, Ireland. **_[kjames@cit.ie](mailto:kjames@cit.ie)_
**Verified Affiliation:**
**Chemistry Department, Cork Institute of Technology, Bishopstown, Ireland.**

## Examples of true positives

**Example 2:**
**OCR Text: **
**The Wailter &i Eli-a Hall Ins.titfte of Medical Researchl, **
**Post Office Box the Royal Melboulrlle Hospital 3050, Victoriat, Atustralia  **
**Found Affiliation:**
**The Walter and Eliza Hall Institute of Medical Research, **
**Post Office Box the Royal Melbourne Hospital 3050, Victoria, Australia.**
**Verified Affiliation:**
**The Walter & Eliza Hall Institute of Medical Research, **
**Royal Melbourne Hospital, Victoria, Australia.**

## Examples of true positives

**Example 3:**
**OCR Text: **
**' Laboratori de Quitnica Farmaceutica, Facultat de Farmacia, **
**Universitat de Barcelona, Avda Diagonal sln, E-08028 Barcelona, Spain**
**b Laboratoire de Chinlie Generale, Consertatoire National des Arts et Mttiers, **
**292, rue Saint-Martin, F-75141 Paris, France**
**Found Affiliation:**
**Laboratori de Qu ́imica Farmac`eutica, Facultat de Farm`acia, **
**Universitat de Barcelona, Spain.**
**Verified Affiliation:**
**Laboratori de Qu ́imica Farmac`eutica, Facultat de Farm`acia, **
**Universitat de Barcelona, Spain.**

## Why we are cautious: Examples of false positives

**Example 1:**
**OCR Text: **
**tDeparttnlent of Vetcriniary Patlhology, Faculty of Agricuilture, **
**Miyazaki University, Miyazaki 889-2155, Japan and **
**bDepartttent of Virology, Instittute of Medical Scienzce, **
**Tihe University of Tokyo, Tokyo, 108-8639, Japan**
**Found Affiliation:**
**Department of Virology, The Institute of Medical Science, **
**The University of Tokyo, Tokyo, Japan.**
**Verified Affiliation:**
**Department of Veterinary Pathology, Faculty of Agriculture, **
**Miyazaki University, Miyazaki,**** ****Japan.**

## Examples of false positives

**Example 2:**
**OCR Text: **
***Departments of Pneumonology and t Oncology and Radiotherapy, **
**Medical University of Gdansk, Poland**
**Found Affiliation:**
**Department of Oncology and Radiotherapy, **
**Medical University of Gdansk, Poland.**** **
**Verified Affiliation:**
**Department of Pneumonology, **
**Medical University of Gdansk, Poland.**

## Examples of false positives

**Example 3:**
**OCR Text: **
**Bone Marroiw and Stem Cell Transplantation Center, **
**Emory University, Atlanta. GA. USA**
**Found Affiliation:**
**Denver, CO 80262, USA. boyer_e@hub.tch.harvard.edu**
**Verified Affiliation:**
**Bone Marrow and Stem Cell Transplantation Center, **
**Emory University, Atlanta, GA, USA.**

## Even harder:Examples of false negatives

**Example 1:**
**OCR Text: **
**Lehrsttuhlt flir Titcrzuicht und Allen,leiler LandlwirtschlaA**
**Found Affiliation:**
**Lehrstuhl fur Tierzucht und Algemeine Landwirtschaftslethe, **
**Universit ̈at M ̈unchen, Germany. **
**Detlef.Pietrowski@gen.vet-med.uni-muenchen.de**
**Verified Affiliation:**
**Lehrstuhl fu ̈r Tierzucht und Algemeine Landwirtschaftslethe, **
**Universit ̈at M ̈unchen, Germany.**

## Examples of false negatives

**Example 2:**
**OCR Text: **
**Zur ch Universty Psych atric Hospital, Zurich Switzeriand**
**Found Affiliation:**
**Zurich University Psychiatric Hospital, Zurich, Switzerland.**
**Verified Affiliation:**
**Zurich University Psychiatric Hospital, Zurich, Switzerland.**

## Remaining Tasks

**Add display and selection capability to the Verification workstation.**
**Clean up Author/Affiliation/ Zip Code table.**
**Refine Similarity Score algorithm.**
**Trim OCR affiliation text**
**Word weighting**
**Other ideas?**

## Add display and selection capability 

**Add display and selection capability **
**to the Verification workstation.**

**Available**
**real estate**

## Any questions?

**Susan Hauser, Electronics Engineer**
**National Library of Medicine**
**301-435-3209**
**Contact:**** ****http://archive.nlm.nih.gov/staff/hauser.php**