Bachelor's thesis
Information retrieval for a web search engine using neural networks and classic methods
Key facts
- Author
- Lucas Imhof
- University
- Hochschule Merseburg
- Faculty
- Fachbereich Ingenieur- und Naturwissenschaften
- First examiner
- Prof. Dr. rer. pol. Uwe Schröter
- Second examiner
- Prof. Dr. rer. nat. habil. Dr. phil. Michael Schenke
- Submitted
- 11 March 2019
- Published
- 28 March 2019
- Length
- 102 pages
- Language
- Deutsch
- Publisher
- Hochschulbibliothek, Hochschule Merseburg
- Handle
- 1981185920/13836
- PPN
- 1662878591
- Licence
- CC BY 4.0
- Keywords
- Information Retrieval · Retrieval-System · Suchmaschine · Bildersuche
Abstract
This bachelor's thesis deals with information retrieval for a web search engine. The quality of the data collected by information retrieval largely determines the efficiency of the search engine that is supposed to deliver results to a user from that data. Quality means that a user receives a result that is useful for the task at hand – data that matches the query both thematically and in content, and that is prioritised correctly depending on several factors discussed in the thesis. Image search is a particular challenge: it cannot simply match keywords, the content of the image has to be analysed and categorised by the retrieval system first.
In parallel to the written thesis, a prototype of a search engine was built. It consists of a crawler network that extracts information from web pages, images and documents and stores it in a database via a server, plus a search engine that lets you search for text fragments and images found by the crawler network. (Translation; the thesis itself is written in German.)
In numbers
102
pages
6
chapters
26
figures
3
tables
27
code listings
7
formulas
88
references
Table of contents
Chapter titles in the original German, page numbers as in the PDF.
Key findings
- 1
Classic text analysis is sufficient for phrase search – neural networks only pay off there once usage data allows a personalised ranking.
- 2
Neural networks are indispensable for image search because people search for image content; image titles and OCR text complement the insufficiently trained network.
- 3
Combining both approaches is the right way to build a web search engine.
- 4
The prototype only scales with clustering, strictly encapsulated modules and a temporary link database in front of the search database.
- 5
A new search engine for Europe would have to be transparent, open source, ad-free, donation-funded and hosted in Europe – and would still hardly stand a chance against the market leaders.
Read the thesis
The published version, served from this site (3.3 MB). No third-party connections.
Official publication
The thesis is published in the open-access repository of the University and State Library of Saxony-Anhalt (Share_it) and permanently citable via DOI and URN. Licence: Creative Commons Attribution 4.0.
How to cite
APA
Imhof, L. (2019). Information Retrieval für eine Web Suchmaschine mithilfe von neuronalen Netzen und klassischen Methoden [Bachelorarbeit, Hochschule Merseburg]. Hochschulbibliothek Merseburg. https://doi.org/10.25673/13738
BibTeX
@thesis{imhof2019zypersearch,
author = {Imhof, Lucas},
title = {Information Retrieval f{\"u}r eine Web Suchmaschine mithilfe von neuronalen Netzen und klassischen Methoden},
type = {Bachelorarbeit},
school = {Hochschule Merseburg},
year = {2019},
month = mar,
doi = {10.25673/13738},
url = {https://opendata.uni-halle.de/handle/1981185920/13836},
note = {Lizenz: CC BY 4.0}
}