Judul: Pseudo-Relevance Feedback on Retrieval Using Sentence Segmentation
Abstrak: A very large amount of information has stimulated the development of search engine to help users in finding information they need. To retrieve information that relevant to the user’s needs, users should be able to formulate queries correctly. Pseudo-relevance feedback is an automatically local analysis technique for improving queries. This technique takes the top n-ranked documents and takes the top x-ranked terms from relevant documents. The purpose of this research is to implement query expansion with pseudo-relevance feedback using sentence segmentation. There are two groups of documents, 1.000 agriculture documents and 93 medicine plants documents which are used. The test result shows that the use of medicine plants documents is better than agriculture documents. This is due to agriculture documents have a high enough similarity between documents. The performance of information retrieval with pseudo-relevance feedback using sentence segmentation gave good result with around 89% average precision for medicine plants documents and 56% for agriculture documents.
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Judul: Pseudo-Relevance Feedback on Retrieval Using Document Segmentation.
Abstrak: Web is the largest information source in the world, but the storage and effective information retrieval on the web is still a problem in this day. Pseudo-relevance feedback is automatically local analysis technique (relevance feedback technique without explicit input user). This technique takes the top n-ranked documents as the relevant documents and takes the top x-ranked terms from relevant documents. Basically, a document consist of any topics, so in the research, relevant documents substituted by a segment which represents a topic in the relevant document. The segment is taken by XML document tag, are <TITLE>, <AUTHOR> and <P> tag, since the text from those tags are usually represent a document. The visual block extraction phase (first step in VIsion based Page Segmentation algorithm), used in segmented the document, so the title of the research is Pseudo-Relevance Feedback on Retrieval Using Document Segmentation. This research done in six phases, there are retrieval initialization, document segmentation, segments selection, terms selection, final retrieval and retrieval output evaluation. The result of system performance is good, that is 0.5214. The test results show that the performance of the PRF based segmentation of documents and without PRF retrieval was not found significant differences. It is because of the taken documents and segments for expansion terms selection are not relevant, expanded queries are not exact representing the segment, the member of documents that are used in retrieval is relatively small, that are 1000 documents. Keywords: pseudo-relevance feedback, relevance feedback, page segmentation, text processing.
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Judul: Kekonsistenan Hamiltonian pada Gerak Gelombang Interfacial
Abstrak: The interfacial wave is an internal wave that occurs at boundary of two layers fluid. It appears because there is difference of mass density between the two layers. The objective of this thesis is to formulate the motion of internal wave with flat base and flat as well as free upper bound surface. The motion equation obtained is a Hamiltonian system. The Hamiltonian in this system is expressed by variable of wave deviation and horizontal component of potential velocity. Under assumption that interfacial wave moves only in one direction, it can be shown that the Hamiltonian depends on the solution of the wave motion equation. The coefficients of the equation depend on the physical characteristics of the two layers of fluid, i.e. thickness and mass density. The numerical results show that Hamiltonian in the system is constant. It is consistent with Hamiltonian characteristic, which does not depend on time.
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