Search (7 results, page 1 of 1)

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Imprint

Potsdam : Fachhochschule, Institut für Information und Dokumentation

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Imprint

Potsdam : Fachhochschule, Institut für Information und Dokumentation

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Abstract

As the Web continues to grow and encompass broader and more diverse sources of information, providing effective search facilities to users becomes an increasingly challenging problem. To help users deal with the deluge of Web-accessible information, we propose a search system which makes use of context to improve search results in a scalable way. By context, we mean any sources of information, in addition to any search query, that provide clues about the user's true information need. For instance, a user's bookmarks and search history can be considered a part of the search context. We consider two types of context-based search. The first type of functionality we consider is "similarity search." In this case, as the user is browsing Web pages, URLs for pages similar to the current page are retrieved and displayed in a side panel. No query is explicitly issued; context alone (i.e., the page currently being viewed) is used to provide the user with useful related information. The second type of functionality involves taking search context into account when ranking results to standard search queries. Web search differs from traditional information retrieval tasks in several major ways, making effective context-sensitive Web search challenging. First, scalability is of critical importance. With billions of publicly accessible documents, the Web is much larger than traditional datasets. Similarly, with millions of search queries issued each day, the query load is much higher than for traditional information retrieval systems. Second, there are no guarantees on the quality ofWeb pages, with Web-authors taking an adversarial, rather than cooperative, approach in attempts to inflate the rankings of their pages. Third, there is a significant amount of metadata embodied in the link structure corresponding to the hyperlinks between Web pages that can be exploitedduring the retrieval process. In this thesis, we design a search system, using the Stanford WebBase platform, that exploits the link structure of the Web to provide scalable, context-sensitive search.

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Abstract

Das Internet mit seinen ständig neuen Usern und seinem extremen Wachstum bringt viele neue Herausforderungen mit sich. Aufgrund dieses Wachstums bedienen sich die meisten Leute der Hilfe von Suchmaschinen um Inhalte innerhalb des Internet zu finden. Suchmaschinen nutzen für die Beantwortung der User-Anfragen Information Retrieval Techniken. Problematisch ist nur, dass traditionelle Information Retrieval (IR) Systeme für eine relativ kleine und zusammenhängende Sammlung von Dokumenten entwickelt wurden. Das Internet hingegen unterliegt einem ständigen Wachstum, schnellen Änderungsraten und es ist über geographisch verteilte Computer verteilt. Aufgrund dieser Tatsachen müssen die alten Techniken erweitert oder sogar neue IRTechniken entwickelt werden. Eine Suchmaschine die diesen Herausforderungen vergleichsweise erfolgreich entgegnet ist Google. Ziel dieser Arbeit ist es aufzuzeigen, wie Suchmaschinen funktionieren. Der Fokus liegt dabei auf der Suchmaschine Google. Kapitel 2 wird sich zuerst mit dem Aufbau von Suchmaschinen im Allgemeinen beschäftigen, wodurch ein grundlegendes Verständnis für die einzelnen Komponenten geschaffen werden soll. Im zweiten Teil des Kapitels wird darauf aufbauend ein Überblick über die Architektur von Google gegeben. Kapitel 3 und 4 dienen dazu, näher auf die beiden Komponenten Crawler und Indexer einzugehen, bei denen es sich um zentrale Elemente im Rahmen von Suchmaschinen handelt.

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Abstract

The current web consists of documents that are highly heterogeneous and hard for machines to understand. The Semantic Web is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.

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Imprint

Hamburg : Hochschule für Angewandte Wissenschaften, FB Bibliothek und Information

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Abstract

Der Ausgangspunkt dieser Arbeit ist die Suchproblematik im World Wide Web. Suchmaschinen sind einerseits unverzichtbar für erfolgreiches Information Retrieval, andererseits wird ihnen eine mäßige Leistungsfähigkeit vorgeworfen. Das Thema dieser Arbeit ist die Untersuchung der Retrievaleffektivität deutschsprachiger Suchmaschinen. Es soll festgestellt werden, welche Retrievaleffektivität Nutzer derzeit erwarten können. Ein Ansatz, um die Retrievaleffektivität von Suchmaschinen zu erhöhen besteht darin, redaktionell von Menschen erstellte und automatisch generierte Suchergebnisse in einer Trefferliste zu vermengen. Ziel dieser Arbeit ist es, die Retrievaleffektivität solcher hybrider Systeme im Vergleich zu rein roboterbasierten Suchmaschinen zu evaluieren. Zunächst werden hierzu die grundlegenden Problembereiche bei der Evaluation von Retrievalsystemen analysiert. In Anlehnung an die von Tague-Sutcliff vorgeschlagene Methodik wird unter Beachtung der webspezifischen Besonderheiten eine mögliche Vorgehensweise erschlossen. Darauf aufbauend wird das konkrete Setting für die Durchführung der Evaluation erarbeitet und ein Retrievaleffektivitätstest bei den Suchmaschinen Lycos.de, AItaVista.de und QualiGo durchgeführt.