Text Retrieval using Self-organised Document Map: The Case of ILRI Digital Library
| dc.contributor.advisor | Teferi Saba, Dereje | |
| dc.contributor.advisor | Amsalu, Saba | |
| dc.contributor.author | Bayeh, Mulugeta | |
| dc.date.accessioned | 2018-11-28T06:07:37Z | |
| dc.date.accessioned | 2023-11-18T12:44:06Z | |
| dc.date.available | 2018-11-28T06:07:37Z | |
| dc.date.available | 2023-11-18T12:44:06Z | |
| dc.date.issued | 2002-06 | |
| dc.description.abstract | The current availability of large collections of full-text documents in electronic form emphasises the need for intelligent information retrieval techniques. Especially in the rapidly growing digital libraries and distributed access, it is important to have automatic methods for exploring document collections. In this study, the WEBSOM method is used with a quarter of century of research publications maintained by the International Livestock Research Institute for this task. The Self- Organising Map (SOM), also known as Kohonen’s feature map (a means for automatically arranging high-dimensional statistical data), is used to position encoded documents onto a map that provides a general view into the text collection. The general view visualises similarity relations between the documents on a two-dimensional map display, which can be utilised in exploring the material rather than having to rely on traditional search expressions. Similar documents become mapped close to each other providing an intuitive mechanism and ease of access for maximising the institute’s digital information and knowledge resources particularly for users with limited domain knowledge. This study also sheds some light on the power of the SOM in solving problems of high-dimensional data. The trained SOM and the user interface are now usable to both browse the collection and to automatically map new documents. It can successfully make a distinction between the various types of documents and efficiently clusters similar publications to near by locations. It is quite evident that the WEBSOM can effectively visualize the results and is thus especially suitable for exploration tasks without the need to come up with search expressions, which may be difficult even with a rather clear idea of the desired information. The method is a major breakthrough with respect to the much harder problem, for which search methods are usually not even expected to offer much support, encountered when there exists only a vague idea of the object of interest. The same hold true if and when the area of interest resides at the outer edges of one’s current knowledge. This full-fledged report presents most of the situations that may be encountered in a project that explores the practical application of a WEBSOM method to solve the basic problem of devising a suitable search expression, which could neither leave out relevant documents, nor produce long listings of irrelevant hits. The report also provides the general context of text retrieval and a detailed discussion on the actual method used in this research in the various sections. The step-by-step procedures and functions used in both encoding the document collection (preprocessing), computation of the Kohonen feature map and the development of the web-based map interface as well as a discussion of the essential results together with the codes used are included in the report. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/14578 | |
| dc.language.iso | en | en_US |
| dc.subject | Text Retrieval | en_US |
| dc.title | Text Retrieval using Self-organised Document Map: The Case of ILRI Digital Library | en_US |
| dc.type | Thesis | en_US |