Generation of similarity knowledge flow for intelligent browsing based on semantic link networks

Luo, Xiangfeng; Xu, Zheng; Li, Qing; Hu, Qingliang; Yu, Jie; Tang, Xinhuai

doi:10.1002/cpe.1460

Cited by 21 publications

(6 citation statements)

References 28 publications

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“…Luo et al proposed the association link network (ALN) to organize the semantic relation of webpages [16], [18], [19], [20]. Liu et al proposed the community discovery method which can be used to find the related nodes in ALN [21] [22].…”

Section: Organizing the Correlated Data Of Sensorsmentioning

confidence: 99%

Building the Data Association Network of Sensors in the Internet of Things

Wei

et al. 2013

Automatika

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Original scientific paperIn the Internet of Things, wireless sensor networks (WSN) is in charge of gathering and transferring environment data. It is an essential work to mine data semantic in WSN in the data derived from sensors to improve the WSN. This paper proposes the Data Association Network of sensors (DAN) to organize the mined association semantic relations among sensors into an effective form. Because DAN holds the rich data semantic of WSN, it can improve WSN in some aspects, such as detecting the abnormal sensors, simulating the data of faulty sensors, or optimizing the topology of WSN. Experimental results show that the proposed method can mine the associated relations among sensor nodes effectively, and the DAN is helpful in solving some problems of WSN. Key words: Data Mining on IoT, Data Association of Sensors, Data Association Network of SensorsIzgradnja podatkovne mreže senzora u Internetu stvari. Govoreći o Internetu stvari, bežična mreža senzora (WSN) ima ulogu prikupljanja i slanja podataka o okolini. Osnovni je zadatak analizirati semantiku podataka u WSN-u u podacima dobivenim sa senzora u svrhu unaprijeenja bežične mreže senzora. U ovom radu predloženo je mrežno udruženje podataka (DAN) sa senzora u svrhu organiziranja analiziranih udruženja semantičkih relacija izmeu senzora u djelotvorne forme. S obzirom da DAN sadrži dosta semantičkih podataka s WSN-a, može unaprijediti WSN u odreenim aspektima kao npr. detekcija neispravnih senzora, simuliranje podataka sa senzora u kvaru ili optimiziranje topologije WSN-a. Eksperimentalni rezultati pokazuju da predložena metoda može efektivno analizirati udružene relacije izmeu senzorskihčvorova te da je DAN korisno u rješavanju odreenih problema WSN-a.Ključne riječi: rudarenje podataka u internetu stvari, udruženje podataka senzora, mrežno udruženje podataka sa senzora

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Section: Organizing the Correlated Data Of Sensorsmentioning

confidence: 99%

Building the Data Association Network of Sensors in the Internet of Things

Wei

et al. 2013

Automatika

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“…The World Wide Web is traditionally viewed as a web of linked documents. A great research effort has been put to the analysis and modeling of the relationships among the individual documents (Page et al, 1999) or even analyzing semantic document relationships in order to obtain more information about the web organization (Luo et al, 2009;Luo et al, 2011). From this point of view, the documents are usually regarded as atomic units with certain properties such as the individual keyword frequencies.…”

Section: Introductionmentioning

confidence: 99%

Extracting Visually Presented Element Relationships from Web Documents

Burget

Smrž

2013

International Journal of Cognitive Informatics and Natural Intelligence

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Many documents in the World Wide Web present structured information that consists of multiple pieces of data with certain relationships among them. Although it is usually not difficult to identify the individual data values in the document text, their relationships are often not explicitly described in the document content. They are expressed by visual presentation of the document content that is expected to be interpreted by a human reader. In this paper, the authors propose a formal generic model of logical relationships in a document based on an interpretation of visual presentation patterns in the documents. The model describes the visually expressed relationships between individual parts of the contents independently of the document format and the particular way of presentation. Therefore, it can be used as an appropriate document model in many information retrieval or extraction applications. The authors formally define the model, the authors introduce a method of extracting the relationships between the content parts based on the visual presentation analysis and the authors discuss the expected applications. The authors also present a new dataset consisting of programmes of conferences and other scientific events and the authors discuss its suitability for the task in hand. Finally, the authors use the dataset to evaluate results of the implemented system.

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“…The study of semantic similarity between words is a problem with a long history both in the academic community and industry. Examples include word sense disambiguation , knowledge flow generation , image retrieval , multimodal documents retrieval , topic detection , and automatic hypertext linking .…”

Section: Introductionmentioning

confidence: 99%

Measuring semantic similarity between words by removing noise and redundancy in web snippets

Luo

et al. 2011

Concurrency and Computation

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SUMMARYSemantic similarity measures play important roles in many Web-related tasks such as Web browsing and query suggestion. Because taxonomy-based methods can not deal with continually emerging words, recently Web-based methods have been proposed to solve this problem. Because of the noise and redundancy hidden in the Web data, robustness and accuracy are still challenges. In this paper, we propose a method integrating page counts and snippets returned by Web search engines. Then, the semantic snippets and the number of search results are used to remove noise and redundancy in the Web snippets ('Web-snippet' includes the title, summary, and URL of a Web page returned by a search engine). After that, a method integrating page counts, semantics snippets, and the number of already displayed search results are proposed. The proposed method does not need any human annotated knowledge (e.g., ontologies), and can be applied Web-related tasks (e.g., query suggestion) easily. A correlation coefficient of 0.851 against Rubenstein-Goodenough benchmark dataset shows that the proposed method outperforms the existing Web-based methods by a wide margin. Moreover, the proposed semantic similarity measure significantly improves the quality of query suggestion against some page counts based methods.

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Generation of similarity knowledge flow for intelligent browsing based on semantic link networks

Abstract: SUMMARY Similarity Knowledge Flow (SKF) is a kind of scientific workflow, providing an effective technique and theoretical support for intelligent browsing in the

Cited by 21 publications

References 28 publications

Building the Data Association Network of Sensors in the Internet of Things

Building the Data Association Network of Sensors in the Internet of Things

Extracting Visually Presented Element Relationships from Web Documents

Measuring semantic similarity between words by removing noise and redundancy in web snippets

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