Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Enhancing Scalable Reverse Dictionary Using Text Rank

Author : Shailesh Raskar 1 Saurabh Nagpal 2 Shubham Das 3 Sharif Sayyed 4

Date of Publication :7th April 2016

Abstract: The huge availability of words in usage is really becoming a challenging task in finding the correct meaning of words. When people think that they could have defined a sentence or a situation much more concisely by using a single word or a smaller phrase. Sometimes people go on describing the situation or a feeling in long sentences. In such situation, the tool reverse dictionary is useful that it gives an appropriate word to one’s sentence. A reverse dictionary is a dictionary which is organized in a nonalphabetical order that provides the user with information that would be difficult to obtain from a traditional alphabetical ordered dictionary. A traditional dictionary accepts input as a word and gives one or more definitions in terms of result. Thus, the concept of reverse dictionary is exactly opposite to that of traditional dictionary. It takes input as a sentence or a phrase describing a concept or situation, and returns a set of precise and appropriate words that satisfy the meaning of the input sentence or phrase. In this project, an implementation of reverse dictionary is proposed which helps the user to get appropriate words to the input phrases.

Reference :

    1. Ryan Shaw, Member, IEEE, Anindya Datta, Member, IEEE, Debra Vander Meer, Member, IEEE, and Kaushik Dutta, Member, IEEE, “Building a Scalable Database-Driven Reverse Dictionary, VOL. 25, NO. 3, MARCH 2013
    2. J. Carlberger, H. Dalianis, M. Hassel, and O. Knutsson, “Improving Precision in Information Retrieval for Swedish Using Stemming,” ,Aug. 2001.
    3. H. Cui, R. Sun, K. Li, M.-Y. Kan, and T.-S. Chua, “Question Answering Passage Retrieval Using Dependency Relations”, pp. 400-407, 2005.
    4. J. Kim and K. Candan, “Cp/cv: Concept Similarity Mining without Frequency Information from Domain Describing Taxonomies,” Proc. ACM Conf. Information and Knowledge Management,2006.
    5. E. Gabrilovich and S. Markovitch, “Wikipedia-Based Semantic Interpretation for Natural Language Processing,” J. Artificial Intelligence Research, vol. 34, no. 1, pp. 443-498, 2009
    6. Rada Mihalcea and Paul Tarau, “Text Rank: Bringing Order into Texts”.

Recent Article