In this paper, we propose a novel method for real estate price prediction using web new media sentiments by incorporating human searching behaivor on the web. By combining online daily news' sentiments and Google ...
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In this paper, we propose a novel method for real estate price prediction using web new media sentiments by incorporating human searching behaivor on the web. By combining online daily news' sentiments and Google search engine query data, we construct a web news content and online search behavior-based integrated model for real estate prediction. Besides these factors, real estate price time series data are also considered into the model in order to improve the forecasting performance. Furthermore, we make a comparison between the integrated model and the baseline model without search engine query data. Experimental results indicate that the integrated model outperforms the non-integrated model, which suggests that online user searching behavior is of great value in enhancing the prediction performance. These findings imply that the proposed integrated model is effective and feasible for real estate market prediction.
Online shopping has been accepted by more and more consumers. C2C websites provide thousands of offers for consumers as a mainstream e-commerce platform. When customers search products in C2C website, some returned of...
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Investigating information needs of elderly people could find out information required to address needs of the aged in a community to present an information service framework to meet their needs. Using data collected f...
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Investigating information needs of elderly people could find out information required to address needs of the aged in a community to present an information service framework to meet their needs. Using data collected from 600 elderly people through field investigation with a questionnaire in a rural community in central China, the results show that the preferred information format of the vast majority of elderly people is audio and/or visual information product, especially audio product. Most of interviewees stated that they were in need of healthy and medical audio information products. The survey maybe lead to improved and expanded information services for respondents who are short of such services, including Public broadcasting services, extending the audiovisual collection, loaning audiovisuals, religious faith audiovisuals and others providing needed information to them. This paper assembles together views on what the elderly people currently need to be helped by both practitioners and researchers in the elderly people services domain.
Due to the rapid growth of social net services (SNSs), research into SNSs continuance usage has recently emerged as an important issue in information systems adaption. This study develops an integrated model based on ...
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Due to the rapid growth of social net services (SNSs), research into SNSs continuance usage has recently emerged as an important issue in information systems adaption. This study develops an integrated model based on the expectation-confirmation model (ECM), the technology acceptance model (TAM), and the theory of planned behavior (TPB), and apply them into the context of older adults' continuance intention toward SNSs. The hypothesized model is validated empirically using a sample collected from 250 older adults who had prior experience with SNSs and was tested against the proposed research model using structure equation modeling. Analysis results demonstrate that satisfaction has the most significant effect on older adults' continuance intention, followed by perceived usefulness, attitude, subject norm and perceived behavioral control. The results of these findings for SNSs practitioners are discussed at the end of this work.
Pseudo-relevance feedback has been perceived as an effective solution for automatic query ***,a recent study has shown that traditional pseudo-relevance feedback may bring into topic drift and hence be harmful to the ...
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Pseudo-relevance feedback has been perceived as an effective solution for automatic query ***,a recent study has shown that traditional pseudo-relevance feedback may bring into topic drift and hence be harmful to the retrieval *** this paper,using the idea of local analysis,an effective XML query expansion method,is presented,which utilizes the local word co-occurrence information in good pseudo-relevance document collection and the structural semantics of XML to select most appropriate expansion *** results on INEX 2005 IEEE-CS collection show that the proposed expansion method offers better retrieval performance,compared with original query.
Filtering redundancy data is an important task of radio frequency identification (RFID) middleware. In order to ensure RFID middleware can effectively filter the time redundant data and identify tagged object location...
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Filtering redundancy data is an important task of radio frequency identification (RFID) middleware. In order to ensure RFID middleware can effectively filter the time redundant data and identify tagged object location change timely, this paper proposed a Temporal-Spatial bloom filter based on the sliding window model. The filter extends the one-dimension array in the standard bloom filter to a two-dimension array. Meanwhile, in order to guarantee the false positive rate doesn't increase due to the reason that the storage unit of the filter becomes full, we proposed a random decay strategy for deleting the expiration elements. The experimental results show that TSBF algorithm can filter time redundant data effectively and had a good performance to deal with location movement.
With the dramatic increase of data volume, automatic data distribution has been one of the key techniques and intractable problem for distributed systems. This work summarizes the problem of data distribution and abst...
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Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other seman...
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Head-driven statistical models for natural language parsing are the most representative lexicalized syntactic parsing models, but they only utilize semantic dependency between words, and do not incorporate other semantic information such as semantic collocation and semantic category. Some improvements on this distinctive parser are presented. Firstly, "valency" is an essential semantic feature of words. Once the valency of word is determined, the collocation of the word is clear, and the sentence structure can be directly derived. Thus, a syntactic parsing model combining valence structure with semantic dependency is purposed on the base of head-driven statistical syntactic parsing models. Secondly, semantic role labeling(SRL) is very necessary for deep natural language processing. An integrated parsing approach is proposed to integrate semantic parsing into the syntactic parsing process. Experiments are conducted for the refined statistical parser. The results show that 87.12% precision and 85.04% recall are obtained, and F measure is improved by 5.68% compared with the head-driven parsing model introduced by Collins.
A survey about the information needs of elderly people could find out the information required to address the needs of the aged in a community. Analyzing data collected from 600 elderly people through
A survey about the information needs of elderly people could find out the information required to address the needs of the aged in a community. Analyzing data collected from 600 elderly people through
The volume of RDF data increases very fast within the last five years, e.g. the Linked Open data cloud grows from 2 billions to 50 billions of RDF triples. With its wonderful scalability, cloud computing platform like...
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