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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
The Fisher kernel is a generic framework which combines the benefits of generative and discriminative approaches to pattern classification. In this contribution, we propose to apply this framework to handwritten word-spotting. Given a word image and a keyword generative model, the idea is to generate a vector which
After analyzing the disadvantages of traditional text clustering method based on keywords set, a novel approach for clustering of Chinese text based on concept hierarchy is presented. It introduces a Chinese topic classify dictionary as background knowledge to clustering of Chinese text. It adopts a hierarchical
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
Adult image detection plays an important role in Internet pornographic information detection and filtering. By analyzing the shortcomings of existing pornographic image detection algorithms depending only on image content or keywords of text, a new adult image detection algorithm fusing image semantic features and
by combining vectors of the named entities and keywords which can express the center vector of the topic more accurately. Then it deals with topic drift by single-pass clustering and continual modification of the topic center. The result of experiments shows that the new method can reduce the rate of missing and false
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
With rapid development of Internet information, It is quite an important project for data mining that how to classify these large amounts of texts. In this paper, we propose an improved text classify cluster algorithm, while calculating similarity, we synthetically consider the relationship between keywords and
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