Topic-based Intelligent Support System for Information Retrieval

2000 ◽  
Vol 4 (6) ◽  
pp. 457-463
Author(s):  
Yasufumi Takama ◽  
◽  
Kaoru Hirota
Keyword(s):  
Information Retrieval ◽  
World Wide ◽  
Vector Space Model ◽  
The Other ◽  
Immune Network ◽  
Intelligent Support ◽  
Space Model ◽  
The World ◽  
Topic Distribution ◽  
Immune Network Model

We propose a new concept of intelligent support systems for topic-based information retrieval. As information retrieval (IR) on the World Wide Web (WWW) becomes widespread, new types of tools and systems that do not only find specific pages the user wants, but also and helping the user learn about a particular field of interest are increasingly needed. Two systems based on this consideration are introduced in this paper. One is the Fish View system for supporting document-ordering. It focuses on the user’s document-ordering (making diagrams) while reading, and the user’s viewpoint is represented by a combination of a small number of concepts taken from the existing concept structure dictionary. The extracted viewpoint can be used for measuring the similarity among documents, using fisheye matching, the extended Vector Space Model. The other is the query network for visualization of the topic distribution through WWW IR, and its concept employing the Immune Network model is introduced with preliminary experiments.

scholarly journals A Topological Method for Comparing Document Semantics

2020 ◽  
Author(s):  
Yuqi Kong ◽  
Fanchao Meng ◽  
Ben Carterette
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Language Processing ◽  
State Of The Art ◽  
Vector Space Model ◽  
The Other ◽  
Space Model ◽  
Topological Persistence ◽  
Art Methods ◽  
Novel Algorithm

Comparing document semantics is one of the toughest tasks in both Natural Language Processing and Information Retrieval. To date, on one hand, the tools for this task are still rare. On the other hand, most relevant methods are devised from the statistic or the vector space model perspectives but nearly none from a topological perspective. In this paper, we hope to make a different sound. A novel algorithm based on topological persistence for comparing semantics similarity between two documents is proposed. Our experiments are conducted on a document dataset with human judges’ results. A collection of state-of-the-art methods are selected for comparison. The experimental results show that our algorithm can produce highly human-consistent results, and also beats most state-of-the-art methods though ties with NLTK.

Aplikasi Deteksi Kemiripan Tugas Paper

2017 ◽  
Vol 15 (2) ◽  
pp. 5
Author(s):  
Anthony Anggrawan ◽  
Azhari
Keyword(s):  
Information Retrieval ◽  
Vector Space ◽  
Vector Space Model ◽  
Mean Average Precision ◽  
Average Precision ◽  
Information Searching ◽  
Space Model ◽  
Model Method

Information searching based on users’ query, which is hopefully able to find the documents based on users’ need, is known as Information Retrieval. This research uses Vector Space Model method in determining the similarity percentage of each student’s assignment. This research uses PHP programming and MySQL database. The finding is represented by ranking the similarity of document with query, with mean average precision value of 0,874. It shows how accurate the application with the examination done by the experts, which is gained from the evaluation with 5 queries that is compared to 25 samples of documents. If the number of counted assignments has higher similarity, thus the process of similarity counting needs more time, it depends on the assignment’s number which is submitted.

On Generalized Vector Space Model in Information Retrieval

1985 ◽  
Vol 8 (2) ◽  
pp. 253-267
Author(s):  
S.K.M. Wong ◽  
Wojciech Ziarko
Keyword(s):  
Information Retrieval ◽  
Vector Space ◽  
A Priori ◽  
Vector Space Model ◽  
Smart System ◽  
Space Model ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Index Terms ◽  
Minimal Modification

In information retrieval, it is common to model index terms and documents as vectors in a suitably defined vector space. The main difficulty with this approach is that the explicit representation of term vectors is not known a priori. For this reason, the vector space model adopted by Salton for the SMART system treats the terms as a set of orthogonal vectors. In such a model it is often necessary to adopt a separate, corrective procedure to take into account the correlations between terms. In this paper, we propose a systematic method (the generalized vector space model) to compute term correlations directly from automatic indexing scheme. We also demonstrate how such correlations can be included with minimal modification in the existing vector based information retrieval systems.

Patterns of Searching for Information on the World Wide Web: A Pilot Study

2003 ◽  
Vol 92 (3_suppl) ◽  
pp. 1091-1096 ◽  
Author(s):  
Nobuhiko Fujihara ◽  
Asako Miura
Keyword(s):  
World Wide Web ◽  
Undergraduate Students ◽  
Search Engines ◽  
World Wide ◽  
Information Sources ◽  
Task Type ◽  
The Other ◽  
The World ◽  
Selection Of ◽  
Search Domain

The influences of task type on search of the World Wide Web using search engines without limitation of search domain were investigated. 9 graduate and undergraduate students studying psychology (1 woman and 8 men, M age = 25.0 yr., SD = 2.1) participated. Their performance to manipulate the search engines on a closed task with only one answer were compared with their performance on an open task with several possible answers. Analysis showed that the number of actions was larger for the closed task ( M = 91) than for the open task ( M = 46.1). Behaviors such as selection of keywords (averages were 7.9% of all actions for the closed task and 16.7% for the open task) and pressing of the browser's back button (averages were 40.3% of all actions for the closed task and 29.6% for the open task) were also different. On the other hand, behaviors such as selection of hyperlinks, pressing of the home button, and number of browsed pages were similar for both tasks. Search behaviors were influenced by task type when the students searched for information without limitation placed on the information sources.

scholarly journals Precedent Names in the Text Field of Marina Tsvetaeva from the Perspective of Free Indirect Discourse

2017 ◽  
Vol 13 (7) ◽  
pp. 142
Author(s):  
Daniya Abuzarovna Salimova ◽  
Olga Pavlovna Puchinina
Keyword(s):  
World Wide ◽  
The Other ◽  
Specific Character ◽  
Free Indirect Discourse ◽  
Personal Names ◽  
Text Field ◽  
Indirect Discourse ◽  
Marina Tsvetaeva ◽  
The World ◽  
The One

The present study is complied with the topical theme “name in the text” and devoted to the problems of how precedent names as the text-forming elements function in the poems and prose works of Marina Tsvetaeva within the framework of free indirect discourse. The authors study various methods and functions of personal names. The authors make conclusions concerning the frequency of precedent names and the specific character of intertextual elements in Tsvetaeva’s text, which, on the one hand, complicates the perception of the text, but on the other hand, promotes including both the poet and the reader into the world-wide cultural and spiritual environment. The ways of introducing the name and the persona, especially within free indirect discourse, specifies the further existence of the name / or its absence in the text.

scholarly journals Geographic Information Retrieval and the World Wide Web: A Match Made in Electronic Space

1997 ◽  
pp. 13-26 ◽  
Author(s):  
David Johnson ◽  
Myke Gluck
Keyword(s):  
Information Retrieval ◽  
World Wide Web ◽  
Information Needs ◽  
World Wide ◽  
Data Retrieval ◽  
Query Languages ◽  
Geographic Information ◽  
Geographic Information Retrieval ◽  
Retrieval Systems ◽  
The World

This article looks at the access to geographic information through a review of information science theory and its application to the WWW. The two most common retrieval systems are information and data retrieval. A retrieval system has seven elements: retrieval models, indexing, match and retrieval, relevance, order, query languages and query specification. The goal of information retrieval is to match the user's needs to the information that is in the system. Retrieval of geographic information is a combination of both information and data retrieval. Aids to effective retrieval of geographic information are: query languages that employ icons and natural language, automatic indexing of geographic information, and standardization of geographic information. One area that has seen an explosion of geographic information retrieval systems (GIR's) is the World Wide Web (WWW). The final section of this article discusses how seven WWW GIR's solve the the problem of matching the user's information needs to the information in the system.

scholarly journals The Performance of Boolean Retrieval and Vector Space Model in Textual Information Retrieval

2017 ◽  
Vol 11 (1) ◽  
pp. 33 ◽  
Author(s):  
Budi Yulianto ◽  
Widodo Budiharto ◽  
Iman Herwidiana Kartowisastro
Keyword(s):  
Information Retrieval ◽  
Vector Space ◽  
Vector Space Model ◽  
Experimental Results ◽  
Inverted Index ◽  
Exact Results ◽  
Textual Information ◽  
Space Model ◽  
Corpus Data

Boolean Retrieval (BR) and Vector Space Model (VSM) are very popular methods in information retrieval for creating an inverted index and querying terms. BR method searches the exact results of the textual information retrieval without ranking the results. VSM method searches and ranks the results. This study empirically compares the two methods. The research utilizes a sample of the corpus data obtained from Reuters. The experimental results show that the required times to produce an inverted index by the two methods are nearly the same. However, a difference exists on the querying index. The results also show that the numberof generated indexes, the sizes of the generated files, and the duration of reading and searching an index are proportional with the file number in the corpus and thefile size.

Cross-Lingual Information Retrieval

2005 ◽  
pp. 153-170 ◽  
Author(s):  
Christopher Yang ◽  
Kar W. Li
Keyword(s):  
Information Retrieval ◽  
Digital Library ◽  
Digital Libraries ◽  
World Wide ◽  
Relevant Information ◽  
Semantic Interoperability ◽  
Library Research ◽  
The World ◽  
Cross Lingual ◽  
Multiple Languages

Structural and semantic interoperability have been the focus of digital library research in the early 1990s. Many research works have been done on searching and retrieving objects across variations in protocols, formats, and disciplines. As the World Wide Web has become more popular in the last ten years, information is available in multiple languages in global digital libraries. Users are searching across the language boundary to identify the relevant information that may not be available in their own language. Cross-lingual semantic interoperability has become one of the focuses in digital library research in the late 1990s. In particular, research in cross-lingual information retrieval (CLIR) has been very active in recent conferences on information retrieval, digital libraries, knowledge management, and information systems. The major problem in CLIR is how to build the bridge between the representations of user queries and documents if they are of different languages.

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