Hybrid Chinese Information Retrieval Model Based on the Combination of Keyword and Concept

A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.

Understanding the role of human-inspired heuristics for retrieval models

Relevance estimation is one of the core concerns of information retrieval(IR)studies.Although existing retrieval models gained much success in both deepening our understanding of information seeking behavior and building effective retrieval systems,we have to admit that the models work in a rather different manner from how humans make relevance judgments.Users’information seeking behaviors involve complex cognitive processes,however,the majority of these behavior patterns are not considered in existing retrieval models.To bridge the gap between practical user behavior and retrieval model,it is essential to systematically investigate user cognitive behavior during relevance judgement and incorporate these heuristics into retrieval models.In this paper,we aim to formally define a set of basic user reading heuristics during relevance judgement and investigate their corresponding modeling strategies in retrieval models.Further experiments are conducted to evaluate the effectiveness of different reading heuristics for improving ranking performance.Based on a large-scale Web search dataset,we find that most reading heuristics can improve the performance of retrieval model and establish guidelines for improving the design of retrieval models with human-inspired heuristics.Our study sheds light on building retrieval model from the perspective of cognitive behavior.

High Efficient Methods of Content-based 3D Model Retrieval

Content-based 3D model retrieval is of great help to facilitate the reuse of existing designs and to inspire designers during conceptual design. However, there is still a gap to apply it in industry due to the low time efficiency. This paper presents two new methods with high efficiency to build a Content-based 3D model retrieval system. First, an improvement is made on the ＂Shape Distribution （D2）＂ algorithm, and a new algorithm named ＂Quick D2＂ is proposed. Four sample 3D mechanical models are used in an experiment to compare the time cost of the two algorithms. The result indicates that the time cost of Quick D2 is much lower than that of D2, while the descriptors extracted by the two algorithms are almost the same. Second, an expandable 3D model repository index method with high performance, namely, RBK index, is presented. On the basis of RBK index, the search space is pruned effectively during the search process, leading to a speed up of the whole system. The factors that influence the values of the key parameters of RBK index are discussed and an experimental method to find the optimal values of the key parameters is given. Finally, ＂3D Searcher＂, a content-based 3D model retrieval system is developed. By using the methods proposed, the time cost for the system to respond one query online is reduced by 75% on average. The system has been implemented in a manufacturing enterprise, and practical query examples during a case of the automobile rear axle design are also shown. The research method presented shows a new research perspective and can effectively improve the content-based 3D model retrieval efficiency.

3D Model Retrieval Method Based on Affinity Propagation Clustering

In order to improve the accuracy and efficiency of 3D model retrieval,the method based on affinity propagation clustering algorithm is proposed. Firstly,projection ray-based method is proposed to improve the feature extraction efficiency of 3D models. Based on the relationship between model and its projection,the intersection in 3D space is transformed into intersection in 2D space,which reduces the number of intersection and improves the efficiency of the extraction algorithm. In feature extraction,multi-layer spheres method is analyzed. The two-layer spheres method makes the feature vector more accurate and improves retrieval precision. Secondly,Semi-supervised Affinity Propagation ( S-AP) clustering is utilized because it can be applied to different cluster structures. The S-AP algorithm is adopted to find the center models and then the center model collection is built. During retrieval process,the collection is utilized to classify the query model into corresponding model base and then the most similar model is retrieved in the model base. Finally,75 sample models from Princeton library are selected to do the experiment and then 36 models are used for retrieval test. The results validate that the proposed method outperforms the original method and the retrieval precision and recall ratios are improved effectively.

NON-LINEAR DYNAMIC MODEL RETRIEVAL OF SUBTROPICAL HIGH BASED ON EMPIRICAL ORTHOGONAL FUNCTION AND GENETIC ALGORITHM

Aiming at the difficulty of accurately constructing the dynamic model of subtropical high, based on the potential height field time series over 500 hPa layer of T106 numerical forecast products, by using EOF（empirical orthogonal function） temporal-spatial separation technique, the disassembled EOF time coefficients series were regarded as dynamical model variables, and dynamic system retrieval idea as well as genetic algorithm were introduced to make dynamical model parameters optimization search, then, a reasonable non-linear dynamic model of EOF time-coefficients was established. By dynamic model integral and EOF temporal-spatial components assembly, a mid-/long-term forecast of subtropical high was carried out. The experimental results show that the forecast results of dynamic model are superior to that of general numerical model forecast results. A new modeling idea and forecast technique is presented for diagnosing and forecasting such complicated weathers as subtropical high.

Three-Dimensional Model Retrieval Using Dynamic Multi-Descriptor Fusion

In this paper, we propose a dynamic multi-descriptor fusion （DMDF） approach to improving the retrieval accuracy of 3-dimensional （3D） model retrieval systems. First, an independent retrieval list is generated by using each individual descriptor. Second, we propose an automatic relevant/irrelevant models selection （ARMS） approach to selecting the relevant and irrelevant 3D models automatically without any user interaction. A weighted distance, in which the weight associated with each individual descriptor is learnt by using the selected relevant and irrelevant models, is used to measure the similarity between two 3D models. Furthermore, a descriptor-dependent adaptive query point movement （AQPM） approach is employed to update every feature vector. This set of new feature vectors is used to index 3D models in the next search process. Four 3D model databases are used to compare the retrieval accuracy of our proposed DMDF approach with several descriptors as well as some well-known information fusion methods. Experimental results have shown that our proposed DMDF approach provides a promising retrieval result and always yields the best retrieval accuracy.

Solid model edit distance: a multi-application and multi-level schema for CAD model retrieval

We present the solid model edit distance(SMED),a powerful and flexible paradigm for exploiting shape similarities amongst CAD models.It is designed to measure the magnitude of distortions between two CAD models in boundary representation(B-rep).We give the formal definition by analogy with graph edit distance,one of the most popular graph matching methods.To avoid the expensive computational cost potentially caused by exact computation,an approximate procedure based on the alignment of local structure sets is provided in addition.In order to verify the flexibility,we make intensive investigations on three typical applications in manufacturing industry,and describe how our method can be adapted to meet the various requirements.Furthermore,a multilevel method is proposed to make further improvements of the presented algorithm on both effectiveness and efficiency,in which the models are hierarchically segmented into the configurations of features.Experiment results show that SMED serves as a reasonable measurement of shape similarity for CAD models,and the proposed approach provides remarkable performance on a real-world CAD model database.

Leaf area index retrieval based on canopy reflectance and vegetation index in eastern China

The aim of this paper is to investigate the feasibility of using Landsat TM data to retrieve leaf area index (LAI). To get a LAI retrieval model based ground reflectance and vegetation index, detailed field data were collected in the study area of eastern China, dominated by bamboo, tea plant and greengage. Plant canopy reflectance of Landsat TM wavelength bands has been inversed using software of 6S. LAI is an important ecological parameter. In this paper, atmospheric corrected Landsat TM imagery was utilized to calculate different vegetation indices (VI), such as simple ratio vegetation index (SR), shortwave infrared modified simple ratio (MSR), and normalized difference vegetation index (NDVI). Data of 53 samples of LAI were measured by LAI-2000 (LI-COR) in the study area. LAI was modeled based on different reflectances of bands and different vegetation indices from Landsat TM and LAI samples data. There are certainly correlations between LAI and the reflectance of TM3, TM4, TM5 and TM7. The best model through analyzing the results is LAI = 1.2097*MSR + 0.4741 using the method of regression analysis. The result shows that the correlation coefficient R2 is 0.5157, and average accuracy is 85.75%. However, whether the model of this paper is suitable for application in subtropics needs to be verified in the future.

基于BLS签名的弹性泄露签名方案(英文)

Digital signature,one of the most important cryptographic primitives,has been commonly used in information systems,and thus enhancing the security of a signature scheme can benefit such an application.Currently,leakage-resilient cryptography is a very hot topic in cryptographic research.A leakage-resilient cryptographic primitive is said to be secure if arbitrary but bounded information about the signer's secret key(involving other states) is leaked to an adversary.Obviously,the leakage-resilient signature is more secure than the common signature.We construct an efficient leakage-resilient signature scheme based on BLS signature in the bounded retrieval model.We also prove that our scheme is provably secure under BLS signature.

Joint shape and color descriptors for 3D urban model retrieval

With the rapid development of photogrammetry,computer vision and three-dimensional(3D)modeling technologies,it is possible to efficiently construct detailed 3D urban models.Accordingly,large corpora of 3D models,such as the Google 3D Warehouse,are now becoming freely available on the web.How to find the proper 3D urban models is a challenging research issue.In this paper,we join shape descriptors and color descriptors for 3D urban model retrieval.The query objects are localized and segmented automatically from the input images by using a new selective search voting algorithm.Through combining the normalization with the light field descriptor,the Horizontal Light Descriptor is introduced to measure the shape similarity among the normalized urban models.The color descriptors are used to represent the color information of the urban models.The two types of descriptors are joined to search 3D urban models similar to the query objects.Experimental results have shown the effectiveness of our approach.

THE STUDY OF RETRIEVAL THEORY AND METHODS FROM SATELLITE REMOTE SENSING FOR METEOROLOGICAL PARAMETERS OVER EASTERN ASIA-PARTI:ISPRM AND SRRM

A review of ten-year's practice in developing the improved simultaneous physical retrieval method(ISPRM)is given in the hope that some creative ideas can be drawn from it.The improvement upon the SPRM is associated with the under-determinedness of this ill-posed inverse problem.In our experiment,the precondition is observed that prior information must be independent of the satellite measurements.The well-posed retrieval theory has told us that the forward process is fundamental for the retrieval,and it is the bridge between the input of satellite radiance and the output of retrievals.In order to obtain a better result from the forward process. the full advantage of every prior information available must be taken.It is necessary to turn the ill- posed inverse problem into the well-posed one.Then by using the Ridge regression or Bayes algorithm to find the optimal combination among the first guess,the theoretical analogue information and the satellite observations,the impact of the under-determinedness of this inverse problem on the numerical solution is minimized.

THE STUDY OF RETRIEVAL THEORY AND METHODS FROM SATELLITE REMOTE SENSING FOR METEOROLOGICAL PARAMETERS OVER EASTERN ASIA—PART Ⅱ:ISPRM AND VSPRM2

Based on the practice of improved simultaneous physical retrieval model(ISPRM),in the light of the functional analysis approach,the variational simultaneous physical retrieval model (VSPRM)has been developed.Its approximation of 1st degree is VSPRM1,which is identical with the ISPRM.Its approximation of 2nd degree is VSPRM2,more advanced than the VSPRM1. This paper has analyzed the function of VSPRM2,pointing out the potentiality of synergy retrieval of this model.Also,it has dealt with the problem of parameterization of water vapor's kernel functions and retrieval of water vapor remote sensing. Because of the characteristics of this strong ill posed inverse problem,prior information must be used wisely in order to get the accurate calculation of radiance R.In the previous paper,we discussed how to build the best first guess field,the way to determine the P_s and to correct the calculation of radiance.In this paper,we continue discussing in depth about the calculation of transmittance,the determination of surface parameters and the selection for an optimum combination of channels for the low-level sounding. The long-term experiment and comparison work under operational environment have shown that the ISPRM is useful for retrieval of temperature and water vapor parameters over China including the Tibetan Plateau,and it further proves the scientific nature of well-posed inverse theory.

Information retrieval:a view from the Chinese IR community

During a two day strategic workshop in February 2018,22 information retrieval researchers met to discuss the future challenges and opportunities within the field.The outcome is a list of potential research directions,project ideas,and challenges.This report describes the major conclusions we have obtained during the workshop.A key result is that we need to open our mind to embrace a broader IR field by rethink the definition of information,retrieval,user,system,and evaluation of IR.By providing detailed discussions on these topics,this report is expected to inspire our IR researchers in both academia and industry,and help the future growth of the IR research community.

3D object retrieval based on histogram of local orientation using one-shot score support vector machine

In this paper, a content based descriptor is pro- posed to retrieve 3D models, which employs histogram of local orientation （HLO） as a geometric property of the shape. The proposed 3D model descriptor scheme consists of three steps. In the first step, Poisson equation is utilized to define a 3D model signature. Next, the local orientation is calculated for each voxel of the model using Hessian matrix. As the final step, a histogram-based 3D model descriptor is extracted by accumulating the values of the local orientation in bins. Due to efficiency of Poisson equation in describing the models with various structures, the proposed descriptor is capable of discriminating these models accurately. Since, the inner vox- els have a dominant contribution in the formation of the de- scriptor, sufficient robustness against noise can be achieved. This is because the noise mostly influences the boundary vox- els. Furthermore, we improve the retrieval performance us- ing support vector machine based one-shot score （SVM-OSS） similarity measure, which is more efficient than the conven- tional methods to compute the distance of feature vectors. The rotation normalization is performed employing the prin- cipal component analysis. To demonstrate the applicability of HLO, we implement experimental evaluations of precision- recall curve on ESB, PSB and WM-SHREC databases of 3D models. Experimental results validate the effectiveness of the proposed descriptor compared to some current methods.

Position based key exchange:definitions and implementations

Chandran,et al.introduce the direction of position based cryptography at CRYPTO 2009.In position based cryptography,the position of a party is used to be its unique“credential”in order to realize the cryptographic tasks,such as position based encryption,position based signature,position based key exchange and so on.Position based key exchange,as a basic primitive in position based cryptography,can be used to establish a shared key based on the position of the participant.To begin with,this paper presents the notions of the prover-to-verifier mode and the prover-to-prover mode for position based key exchange.In the prover-to-verifier mode,a secret key can be shared between a prover and the verifiers according to the position of the prover.While in the prover-to-prover mode,two provers located at the valid positions can negotiate a shared key with the help of the verifiers and any other party whose position is illegal cannot obtain the shared key.At the same time,this paper formalizes two security definitions against colluding adversaries:position based prover-to-verifier key exchange and position based prover-to-prover key exchange.Then,this paper introduces the bounded retrieval model and the implementations of position based key exchange in two modes based on the bounded retrieval model.Finally,this paper discusses the position based key exchange protocols in two modes from both security and performance perspectives.