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methods for Indonesian corpus is rather small. Brace well's algorithm has been proven effective in identifying topics in English and Japanese corpora with high accuracy. This paper implements a method for TID based on Brace well's keywords similarity algorithm and the top-n keywords selection for Indonesian news documents
using feature vector. We do static analysis over computed features to get distinguishing feature descriptors. Maximum similarity i.e. minimum distance allows us to find the query relevant combined pictures and associated relevant words. For textual part of the query we compute the concepts (keywords as well as synonyms of
overloaded sites for a short piece of information of their interest. The crawler developed in the system gathers web page information which is processed using Natural Language Processing and Procedure programming for a specific keyword. The system returns precise short string answers or list to natural language questions
task of ad hoc information retrieval is, finding documents within a corpus like Bible, that are relevant to the user remains a hard challenge. Sometimes the relevant documents may not contain the specified keyword. The lack of the given term in a document does not necessarily mean that the document is not a relevant
components rather than a single Database table. So to minimise the time constraint, memory space and to do a smart search a new IR system is introduced. In the proposed system, searches can be divided into three categorise, namely (i) Main topic search (ii) Subtitle search and (iii) Keyword search. So the system would search
In usual Information Retrieval (IR) systems, the user query is represented in the form of a keyword set. Information resources are retrieved according to their similarities to this query. Consequently if query is not declared with appropriate terms, retrieved results would not be satisfactory. Therefore query
This paper's research work mainly pays attention to the requirement consistency validation. In order to solve the consistency evaluation and multi-branch selection problem during requirement validation process, this paper proposes a kind of requirement measurement method. At first, this paper proposes a keywords
In this paper we present our recent work in implementing Serbian spoken dialogue system for the bus information retrieval at the main Belgrade bus station. Dialogue is organized into several levels. At each level, system has to recognize a limited number of keywords in continuous speech of Serbian. The keywords were
This article describes an algorithm to facilitate the proper assignment of reviewers by finding an author's profile. It uses an original approach to analyzing publications published in digital libraries to get additional keywords based on NLP (natural language processing) techniques. Comparing profiles and finding
The exploitation of social networks and collaborative systems is a phenomenon that is gradually integrated with the practice of information retrieval on the Internet. These systems of Web 2.0, allowing users to collaborate via the free content indexing using keywords or tags; creating structures represented as
order to collect and index only related Web documents. As requests can be insufficient to express sensitive and specific needs, the user's information needs are specified using user's interests represented by DBPedia resources [1] and keywords, both extracted from Web pages provided by the user. A series of experiments
In Digital Library (DL) system, users interact with the system to search for books or research papers. Users can search through metadata or search for information in the pages by querying using keywords. In both cases, a huge amount of results are returned; however, the relevant ones to the user are not often amongst
-defined queries in selected biological published papers during the last five decades. So, in order to evaluate the results, three different data sets were collected and four vectors of selected keywords were considered as the four queries. "Title", "Published date" and the "Abstract
term-by-document matrix, it inevitably loses the information of relations between query terms in the document in the first place. This paper presents a modified vector space model for measuring similarity between the query and the document when responding to a multi-term query. More weight is assigned to the keywords
This paper proposes a new algorithm for retrieving sound based on successive relative search. In retrieving musical sound focusing on its sound features, emotional representations are more appropriate than conventional keywords of the genre or the composer. A vector-based sound retrieval system "Sound Advisor" was
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