Evaluating the accuracy of HMM-based and SVM-based spotters in detecting keywords and recognizing the true place of keyword occurrence shows that the HMM-based spotter detects the place of occurrence more precisely than the SVM-based spotter. On the other hand, the SVM-based spotter performs much better in detecting
documents related to a special keyword. Searchable encryption is a tool for data owners to encrypt their data in a searchable manner. Generally, there exist two kinds of searchable encryption, namely symmetric (secret key) and asymmetric (public key) ones. Most of the public key searchable encryption schemes are vulnerable to
search tools will make it easier for them to learn course subject matter at their own pace. As a first step in this direction, we seek to help instructors create an index for their lecture videos using audio keyword search, with queries recorded by the instructor on their laptop and/or created from video excerpts. For this
As a large number of corpuses are represented, stored and published in XML format, how to find useful information from XML databases has become an increasingly important issue. Keyword search enables web users to easily access XML data without the need to learn a structured query language or to study complex data
articles display notable differences in the types and usage of keywords in the two journals. We conclude that articles published in so‐called predatory journals do not conform to linguistic norms used in higher‐quality journals. These findings may demonstrate a lack of quality control in predatory journals but may also
and lengths of the features including keywords, n grams, skip grams, and bags-of-words. The correlation results are enhanced significantly as the highest correlation scores have increased from 0.22 to 0.70, and the average correlation scores have increased from 0.22 to 0.60.
related keywords as representative vectors for different sentiments, we use these vectors as the sentiment classifier for the testing set. We achieved results that are not only comparable to traditional methods like Naïve Bayes and SVM, but also outperform Latent Dirichlet Allocation, TF-IDF and its variant. It also
digital library. We present Kikori-KS, an effective and efficient XML information retrieval system for scholartic articles. Kikori-KS accepts a set of keywords as a query. This form of query is simple yet useful because users are not required to understand XML query languages or XML schema. To meet practical demands for
) preferences of the user with respect to a set of keywords. These preferences may then be used to rank the daily news, so that the user is recommended those items that match better with his/her interests. The cyclic preference learning methodology described in this paper is illustrated with a case example based on real news from
A search engine shall be obliged to stop the automatic suggestion of keywords directing to websites offering copyright infringing content in association with search queries, given its ability to make copyright infringing activities more difficult on the Internet.
reduced model without having random effect components. It captures the heterogeneous advertising responses across the products as well as search keywords. Our results have implications for online advertising effect measurement, and may help guide advertisers in decision-making.
of keywords in the CallHome telephone speech database. A pair-wise comparison between the feature set of an unknown word utterance and that of each of the reference utterances in a dynamic time warping process showed a false negative score of 4 out of 12, and a false positive score of 5 out of 132 for a subset of speech
new notion called statistics privacy, i.e., the property that predicate privacy is preserved even when the statistical distribution of keywords is known. The second scheme we proposed makes a tradeoff between statistics privacy and storage efficiency (of the delegate). Compared to PEKS, both schemes introduce reasonable
This paper presents the preliminary results of work carried out for recognizing certain keywords using perceptually significant spectral energy features. Dynamic time warping and artificial neural networks were used for feature matching. Preliminary results indicate that the significant energy features are feasible as
On-line information services have become widespread in the Web nowadays. However, Web users are non-specialized and have a great variety of interests. Interfaces for Web databases must, therefore, be both simple and uniform. In this paper, we present a solution for querying Web databases using keywords only. A
Text-based search queries reveal user intent to the search engine, compromising privacy. Topical Intent Obfuscation (TIO) is a promising new approach to preserving user privacy. TIO masks topical intent by mixing real user queries with dummy queries matching various different topics. Dummy queries are generated using a Dummy Query Generation Algorithm (DGA).
In this paper, we propose a keyword spotting system for Korean document images and compare the proposed system with an OCR-based document retrieval system. The system is composed of character segmentation, feature extraction for the query keyword, and word-to-word matching. In the character segmentation step, we
encrypted database. This enables the cloud to reply to a request with a more precise response without compromising any privacy in terms of email contents and also in terms of access patterns. We provide a solution for the email scenario in which we can tag or associate emails with some keywords, and during retrieval, the email
Automatic image annotation plays a critical role in modern keyword‐based image retrieval systems. For this task, the nearest‐neighbor–based scheme works in two phases: first, it finds the most similar neighbors of a new image from the set of labeled images; then, it propagates the keywords associated with the
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”.