Most of the mobile platforms provide a keyword based full text search (FTS) for users to find what they want. However, FTS has difficulties in dealing with the cases where a user cannot remember the exact keywords about target data or the number of search results is too many. To overcome these limitations of FTS, we
Spotting keywords in handwritten documents without transcription is a valuable method as it allows one to search, index, and classify such documents. In this paper we show that keyword spotting based on bi-directional Long Short-Term Memory (BLSTM) recurrent neural nets can successfully be applied on online
. This paper presents an initial study using n-best recognition hypotheses for two tasks, extractive summarization and keyword extraction. We extend the approach used on 1-best output to n-best hypotheses: MMR (maximum marginal relevance) for summarization and TFIDF (term frequency, inverse document frequency) weighting for
evaluate the collection of words and phrases to select set of keywords of the text. Next use the normal search engine to search the keywords set. Part of the search result will be used as seed links in focused crawler. Focused crawler's crawling policy is the best-first search policy, and this policy uses the similarity
Document Summarization (ADS) systems are suitable for the task of outlining useful data. The ADS system model takes a text document as input, and outputs a semantically-relevant summary of this information. This information can be further separated and outlined as keywords, or keyphrases. This paper proposes a novel
This paper proposes a Bag of Visual Words (BoVW) based approach for keyword spotting on the Mongolian historical document images. In this paper, the first step is dividing the scanned Mongolian historical document images into word images by some preprocessing steps, such as connected component analysis, binarization
Keyword search for smallest lowest common ancestors (SLCAs) is an important approach to identify interesting data nodes in XML documents. With the rapid growth of XML data in Internet, how to effectively process massive XML data becomes an interesting topic. As an open-source cloud computing platform developed in
Keyword auctions are being used to sell the positions along the side of organic results shown by search engine when user types a keyword or a query related to keyword in a search engine. It has been a huge revenue generating arena for search engines since last decade. Irrespective of the great success of these types
In the last three decades, engineering education research (EER) has made remarkable progress towards a field of interdisciplinary scholarship. This paper defines EER by developing a keyword-based scheme for exploring EER-related scientific publications and collaboration. The keyword-based scheme refers to a conceptual
Keyword search query processing is considered as the most promising way of information retrieval over XML data in present days as it relieves user from understanding complex schemas of XML document and writing difficult queries using XPath and XQuery. Till date various query processing techniques have been proposed to
Text classification is a useful task in text mining. Most researchers employ one word weight type in the text classification. Here, we proposed to build a keyword list by combining several word weights for a rule based multi label text classification. Through this research, we conducted experiments on the term
In Keyword Search, the system scores belonging to different keywords vary in range due to the characteristics of the keyword and the audio that we search in. However, system decision of a given hit being relevant or irrelevant is made using the same threshold for all keywords. Hence the normalization of the scores of
In general, content-based recommender systems use a keyword vector to locate recommendations. However, this method does not consider relations of each keyword and it is also inscrutable to users, who may have a hard time determining which words in their profiles are important and which may be skewing their results to
The main objective of this work is to classify Hindi stories into three genres: fable, folk-tale and legend. In this paper, we are proposing a framework for story classification using keyword and Part-of-speech (POS) based features. Keyword based features like Term Frequency (TF) and Term Frequency Inverse Document
As the engineering education literature has proliferated across disciplines and continents, the growing number of publications has become difficult to navigate. Recognizing the need to better find and organize publications, authors, and reviewers, Doctors Cindy Finelli and Maura Borrego led an inclusive effort to develop a taxonomy of engineering education terms from a United States perspective. They...
An extracting method of research trend in the field of computer network via analysis of the keywords contained in the published paper of related conferences is presented. The recent trends related to the field of IT are extracted by exploiting the Netminer which is one of the software for analysis of social networks
The energy policies and environmental issues require novel solutions to generate electricity in a challenging and efficient way. The sustainable and reliable grid operations are related to demand management as well as generation. One of the most important requirements to build smarter grids is including smart metering to the power system. The smart grid is not only considered to provide essential...
Traditional keyword-based document clustering techniques have limitations due to simple treatment of words and hard separation of clusters. In this paper, we introduce named entities as objectives into fuzzy document clustering, which are the key elements defining document semantics and in many cases are of user
With the development of Internet, more and more on-line information has become precious wealth that we can access to. High quality information is often stored in dedicated digital libraries. However, query system of most digital libraries based on keyword matching couldnpsilat make users satisfied. This paper presents
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.