Matching Retrieval Research Articles

Terahertz band simulations using two different radiative transfer models

A high-resolution dual-band terahertz (THz) radiometer was designed to measure vertical distributions of chemical elements in the middle atmosphere of the Tibetan Plateau. A forward simulation, which always should be conducted firstly for the development of a matching retrieval algorithm, has not been done before. We use two radiative transfer models, ARTS and AM, to simulate the water vapor, ozone and carbon monoxide spectra on the plateau based on the spectral design of the THz radiometer. The emission line characteristics of the three gases in this spectral band are identified. Reasons for the differences in the spectral simulations between the two models are analyzed for individual gases. The impact of several different spectral parameter settings on the simulations are evaluated through a series of sensitivity experiments. This study suggests that the ARTS is more suitable for the development of the THz radiometer retrieval algorithm. An optimal parameter setting of the ARTS for the three elements are given.

RETRACTED ARTICLE: Application of improved chaos theory genetic multi feature matching algorithm in patent retrieval

The patent retrieval needs to face a large amount of data, and in order to achieve high precision and rapid retrieval, this paper carries out multiple feature matching retrieval by combining the chaos theory and genetic algorithm. Traditional patent retrieval is based on the similarity of semantic key words, and the effect is single and fixed. The genetic algorithm has the function of adaptive intelligent search. It can search the patent database adaptively according to user interest, and the search efficiency is higher. According to the patent search, the search domain of multi feature dimension is established, and the key content of interest is found in the search domain, and the retrieval purpose is realized more accurately by multi dimension matching fusion. Finally, the patent database is established by simulation, and the simulation of different retrieval conditions is carried out. The performance of the algorithm in the convergence speed, the search accuracy and so on is verified, and the application prospect and significance of this algorithm in patent retrieval are also studied.

Robust local feature descriptor for multisource remote sensing image registration

Distinctive and robust local feature description is crucial for remote sensing application, such as image matching and image retrieval. A descriptor for multisource remote sensing image matching that is robust to significant geometric and illumination differences is presented. In the proposed method, a traditional scale-invariant feature transform algorithm is applied for local feature extraction and a feature descriptor, named robust center-symmetric local-ternary-pattern (CSLTP) based self-similarity descriptor, is constructed for each extracted feature point. The main idea of the proposed descriptor is a rotation invariance description strategy on local correlation surface. Unlike common distribution-based descriptors or geometric-based spatial pooling descriptors, the proposed descriptor uses rotation invariance statistically strategic for CSLTP description on a correlation surface, which is inherently rotation invariant and robust to complex intensity differences. Then, a bilateral matching strategy followed by a reliable outlier removal procedure in the geometric transformation model is implemented for feature matching and mismatch elimination. The proposed method is successfully applied for matching various multisource satellite images and the results demonstrate its robustness and discriminability compared to common local feature descriptors.

IR evaluation methods for retrieving highly relevant documents

This paper proposes evaluation methods based on the use of non-dichotomous relevance judgements in IR experiments. It is argued that evaluation methods should credit IR methods for their ability to retrieve highly relevant documents. This is desirable from the user point of view in modem large IR environments. The proposed methods are (1) a novel application of P-R curves and average precision computations based on separate recall bases for documents of different degrees of relevance, and (2) two novel measures computing the cumulative gain the user obtains by examining the retrieval result up to a given ranked position. We then demonstrate the use of these evaluation methods in a case study on the effectiveness of query types, based on combinations of query structures and expansion, in retrieving documents of various degrees of relevance. The test was run with a best match retrieval system (In- Query I) in a text database consisting of newspaper articles. The results indicate that the tested strong query structures are most effective in retrieving highly relevant documents. The differences between the query types are practically essential and statistically significant. More generally, the novel evaluation methods and the case demonstrate that non-dichotomous relevance assessments are applicable in IR experiments, may reveal interesting phenomena, and allow harder testing of IR methods.

Retrieval-induced forgetting is retrieval-modality specific: Evidence from motor memory

Three experiments examined the impact of matching retrieval modality at retrieval practice and at test on retrieval-induced forgetting. Participants learned sequential finger movements to be performed either with the left or with the right index finger. Subsequently, they selectively practiced half the items of one hand. A final recall test then assessed memory for all initially learned items. We contrasted different retrieval modalities. In Experiment 1, retrieval practice pertained to motor responses in one experimental condition but it pertained to visual sequence displays in another condition. The final recall test was motoric in both conditions. In Experiment 2, retrieval practice always pertained to visual sequence displays but the final recall test either pertained to motor responses or to visual sequence displays. Retrieval-induced forgetting emerged only when the modality of the final recall test matched the modality of retrieval practice. In Experiment 3, retrieval practice either involved executing motor sequences with the same finger as in the learning phase or participants had to use the opposite hand for indicating sequences. An effector change for retrieval practice eliminated retrieval-induced forgetting in a test requiring the execution of motor sequences again with the same finger as in the learning phase. We suggest that retrieval-induced forgetting occurred as a consequence of retrieval-modality-specific inhibition.

Efficient Clinical Concept Extraction in Electronic Medical Records

Automatic identification of clinical concepts in electronic medical records (EMR) is useful not only in forming a complete longitudinal health record of patients, but also in recovering missing codes for billing, reducing costs, finding more accurate clinical cohorts for clinical trials, and enabling better clinical decision support. Existing systems for clinical concept extraction are mostly knowledge-driven, relying on exact match retrieval from original or lemmatized reports, and very few of them are scaled up to handle large volumes of complex, diverse data. In this demonstration we will showcase a new system for real-time detection of clinical concepts in EMR. The system features a large vocabulary of over 5.6 million concepts. It achieves high precision and recall, with good tolerance to typos through the use of a novel prefix indexing and subsequence matching algorithm, along with a recursive negation detector based on efficient, deep parsing. Our system has been tested on over 12.9 million reports of more than 200 different types, collected from 800,000+ patients. A comparison with the state of the art shows that it outperforms previous systems in addition to being the first system to scale to such large collections.

Plasma membrane insertion of epithelial sodium channels occurs with dual kinetics.

The epithelial sodium channel (ENaC) constitutes the rate-limiting step for Na(+) transport across electrically tight epithelia. Regulation of ENaC activity is critical for electrolyte and extracellular volume homeostasis, as well as for lung liquid clearance and colon Na(+) handling. ENaC activity is tightly controlled by a combination of mechanisms involving changes in open probability and plasma membrane abundance. The latter reflects a combination in channel biosynthesis and trafficking to and from the membrane. Studying ENaC trafficking with different techniques in a variety of expression systems has yielded inconsistent results, indicating either fast or slow rates of insertion and retrieval, which range from the order of minutes to several hours. Here, we use Xenopus oocytes as ENaC expression system to study channel insertion rate in the membrane using two different techniques under comparable conditions: (1) confocal microscopy coupled to fluorescence recovery after photobleaching (FRAP) measurements; and (2) fluorescent bungarotoxin (BTX) binding to ENaC subunits modified to include BTX binding sites (BBSs) in their extracellular domain, a technique that has not been previously used to study ENaC trafficking. Our confocal-FRAP data indicate a fast rate of ENaC incorporation to the membrane in a process conditioned by channel subunit composition. On the other hand, BTX binding experiments indicate much slower channel insertion rates, with matching slow ENaC retrieval rates. The data support a model that includes fast recycling of endocytosed ENaC with parallel incorporation of newly synthesized channels at a slower rate.

Delayed Match Retrieval: a novel anticipation-based visual working memory paradigm.

We tested 8- and 10-month-old infants' visual working memory (VWM) for object-location bindings - what is where - with a novel paradigm, Delayed Match Retrieval, that measured infants' anticipatory gaze responses (using a Tobii T120 eye tracker). In an inversion of Delayed-Match-to-Sample tasks and with inspiration from the game Memory, in test trials, three face-down virtual 'cards' were presented. Two flipped over sequentially (revealing, e.g. a swirl pattern and then a star), and then flipped back face-down. Next, the third card was flipped to reveal a match (e.g. a star) to one of the previously seen, now face-down cards. If infants looked to the location where the (now face-down) matching card had been shown, this was coded as a correct response. To encourage anticipatory looks, infants subsequently received a reward (a brief, engaging animation) presented at that location. Ten-month-old infants performed significantly above chance, showing that their VWM could hold object-location information for the two cards. Overall, 8-month-olds' performance was at chance, but they showed a robust learning trend. These results corroborate previous findings (Kaldy & Leslie, 2005; Oakes, Ross-Sheehy & Luck, 2006) and point to rapid development of VWM for object-location bindings. However, compared to previous paradigms that measure passive gaze responses to novelty, this paradigm presents a more challenging, ecologically relevant test of VWM, as it measures the ability to make online predictions and actively localize objects based on VWM. In addition, this paradigm can be readily scaled up to test toddlers or older children without significant modification.

Answering keyword queries through cached subqueries in best match retrieval models

Caching is one of the techniques that Information Retrieval Systems (IRS) and Web Search Engines (WSEs) use to reduce processing costs and attain faster response times. In this paper we introduce Top-K SCRC (Set Cover Results Cache), a novel technique for results caching which aims at maximizing the utilization of cache. Identical queries are treated as in plain results caching (i.e. their evaluation does not require accessing the index), while combinations of cached sub-queries are exploited as in posting lists caching, however the exploited subqueries are not necessarily single-word queries. The problem of finding the right set of cached subqueries to answer an incoming query, is actually the Exact Set Cover problem. This technique can be applied in any best match retrieval model that is based on a decomposable scoring function, and we show that several best-match retrieval models (i.e VSM, Okapi BM25 and hybrid retrieval models) rely on such scoring functions. To increase the capacity (in queries) of the cache only the top-K results of each cached query are stored and we introduce metrics for measuring the accuracy of the composed top-K answer. By analyzing queries submitted to real-world WSEs, we verified that there is a significant proportion of queries whose terms is the result of a union of the terms of other queries. The comparative evaluation over traces of real query sets showed that the Top-K SCRC is on the average two times faster than a plain Top-K RC for the same cache size.

Balanced compact clustering for efficient range queries in metric spaces

Given a set of points in a metric space, an additional query point and a positive threshold, a range query determines the subset of points whose distance from the query point does not exceed the given threshold. This paper tackles the problem of clustering the set of points so as to minimize the number of distance evaluations required by a range query. This problem models the efficient extraction of information from a database when the user is not interested in an exact match retrieval, but in the search for similar items. Since this need has become widespread in the management of text, image, audio and video databases, several data structures have been proposed to support such queries. Their optimization, however, is still left to extremely simple heuristic rules, if not to random choices. We propose the Balanced Compact Clustering Problem (BCCP) as a combinatorial model of this problem. We discuss its approximation properties and the complexity of special cases. Then, we present two Integer Programming formulations, prove their equivalence and introduce valid inequalities and variable fixing procedures. We discuss the application of a general-purpose solver on the more efficient formulation. Finally, we describe a Tabu Search algorithm and discuss its application to randomly generated and to real-world benchmark instances up to one hundred thousands points.

Process of Assembling Component Based on Domain Ontology

This paper introduced the related knowledge of domain ontology, analyzed the present situation of assembling component and the steps, and gave out a new assembly process of Domain Ontology Based Assembling Process (DOBAP). In addition, it introduced the overall framework of the system. In addition, System component classification engine based on domain ontology, component matching retrieval and component interface matching verification module are explained in detail. What’s more, traditional component retrieval and matching algorithm of domain ontology based on domain ontology is also improved.

A lattice-based approach for mathematical search using Formal Concept Analysis

Mathematical (or math) search is a challenging problem as math expressions are highly symbolic and structured. The vast majority of math search systems that adopt conventional text retrieval techniques are ineffective in searching math expressions. In this paper, we propose a lattice-based approach for math search. The proposed approach is based on Formal Concept Analysis (FCA), which is a powerful data analysis technique. In the proposed approach, math expressions are first converted into the corresponding MathML representation, from which math features are extracted. Next, the extracted features are used to construct a mathematical concept lattice. At the query time, the query expression is processed and inserted into the mathematical concept lattice, and the relevant expressions are retrieved and ranked. Finally, search results can be visualized and nevigated via a dynamic graph, thanks to the lattice structure. The proposed lattice-based math search approach is benchmarked against a conventional best match retrieval technique and results show it to be almost 10% better in terms of F1 for the top 30 retrieved results.

Research of Automobile Quality Fault Diagnosis Method Based on CBR

CBR (Case-based reasoning) theory is applied to the automobile quality fault diagnosis field. Case description, case retrieve and case reuse are the main factors of CBR. It is realized by the methods of fault tree construction, discrete cases information entropy weight value calculation, discrete and multi-level semantic matching case retrieval and knowledge difference driving case reuse. The process of solving actual cases verify the validity and efficiency of CBR method in the quality fault diagnosis system.

Information Seeking Behaviour of Learner in an Open University Libraries: Issues and Challenges

Information Seeking is the process or activity of attempting to obtain information in both human and technological contexts. Information seeking is related to, but yet different from, information retrieval (IR). Much library and information science research is focused on the information seeking practices of practitioners in various fields of professional work. Studies have been carried out on the information seeking behaviour of librarians, academics, medical professionals, engineers and lawyers. Much of this research has been drawn on the work done by Leckw, Petttigrew and Sylvain, who in 1996 conducted an extensive review of the library and information science literature on information seeking behavior of professionals. Some experts report on a study concerned with understanding people‟s adaptation to new information searching environments. The experts have investigated how people with varying degrees of familiarity with information retrieval systems and varying models of information retrieval processes, interacted in an information retrieval system which did not support exact match retrieval with structured queries, but which did support best match ranked output retrieval with unstructured queries and automatic relevance feedback. The results include a classification of normal information retrieval strategies, the description of several adaptation strategies and the relationships between type and strength of people‟s mental models of information retrieval and their searching behaviours in the new information retrieval context.

Three‐dimensional volcanic aerosol dispersal: A comparison between Multiangle Imaging Spectroradiometer (MISR) data and numerical simulations

The three‐dimensional reconstruction of volcanic plumes is a central goal to enhance our understanding on dispersal processes. In this paper we use data from the Multiangle Imaging Spectroradiometer (MISR) on board NASA's Terra spacecraft combined with a stereo matching retrieval procedure. We show the potential of MISR in capturing important features of volcanic plumes like column height, optical depth, type, and shape of the finest particles of two highly explosive eruptions occurring on Mount Etna in 2001 and 2002. This work tests how tephra dispersal models reconstruct the 3‐D shape of volcanic clouds. We compare MISR data with FALL3D, an Eulerian model for the transport and deposition of volcanic ash and aerosols coupled with the Weather Research and Forecasting mesoscale meteorological model. Agreement between simulations and MISR data is good regarding both events, although it could be improved by increasing the accuracy of the meteorological data, a better constraint on volcanological input parameters like the height of the eruptive column and improving our understanding of processes such as aggregation phenomena and volcanic cloud microphysics.

An illumination and highlights invariant colour model for image matching

Colour can provide critical information for a variety of computer vision tasks such as image matching, object recognition and image retrieval. However, for it to be useful in practice, the colour model used to represent the intrinsic properties of the imaged objects must be insensitive of imaging conditions such as lighting geometry, illumination colour and highlights. In this paper, we present a colour model for image matching and object recognition that is invariant for illumination and highlights. The colour model is defined as the ratios of the colour differences between neighbouring pixels for each colour component. Based on the dichromatic reflection colour model, it is shown that the proposed colour model is invariant to lighting geometry, illumination colour, highlights and diffuse lighting. Experimental results show robust image matching using the proposed colour model on objects that are illuminated under different illumination colours and lighting geometry. The proposed colour model can be used as a prepossessing step for applications where limited or no constraints on the imaging process can be imposed.

Inter and intra-document contexts applied in polyrepresentation for best match IR

The principle of polyrepresentation offers a theoretical framework for handling multiple contexts in information retrieval (IR). This paper presents an empirical laboratory study of polyrepresentation in restricted mode of the information space with focus on inter and intra-document features. The Cystic Fibrosis test collection indexed in the best match system InQuery constitutes the experimental setting. Overlaps between five functionally and/or cognitively different document representations are identified. Supporting the principle of polyrepresentation, results show that in general overlaps generated by three or four representations of different nature have higher precision than those generated from two representations or the single fields. This result pertains to both structured and unstructured query mode in best match retrieval, however, with the latter query mode demonstrating higher performance. The retrieval overlaps containing search keys from the bibliographic references provide the best retrieval performance and minor MeSH terms the worst. It is concluded that a highly structured query language is necessary when implementing the principle of polyrepresentation in a best match IR system because the principle is inherently Boolean. Finally a re-ranking test shows promising results when search results are re-ranked according to precision obtained in the overlaps whilst re-ranking by citations seems less useful when integrated into polyrepresentative applications.

High performance bio-image database retrieval using MPI

Fast and accurate 3D object reconstruction and partial 3D component retrieval from 2D image slices represent a difficult and challenging problem. To group related objects on different layers in an image stack, image segmentation and sequential matching of adjacent 2D objects have to be preformed. Object matching involves heavy computing and is time consuming. In this paper, we propose a new approach for parallel implementation of object contour matching and partial 3D component retrieval based on image contour structure. The method has been implemented in MPI on a SGI Origin 2000 machine. The experimental results show a good speedup for sequential object matching and partial 3D component retrieval.

Experiments with transitive dictionary translation and pseudo‐relevance feedback using graded relevance assessments

AbstractIn this article, the authors present evaluation results for transitive dictionary‐based cross‐language information retrieval (CLIR) using graded relevance assessments in a best match retrieval environment. A text database containing newspaper articles and a related set of 35 search topics were used in the tests. Source language topics (in English, German, and Swedish) were automatically translated into the target language (Finnish) via an intermediate (or pivot) language. Effectiveness of the transitively translated queries was compared to that of the directly translated and monolingual Finnish queries. Pseudo‐relevance feedback (PRF) was also used to expand the original transitive target queries. Cross‐language information retrieval performance was evaluated on three relevance thresholds: stringent, regular, and liberal. The transitive translations performed well achieving, on the average, 85–93% of the direct translation performance, and 66–72% of monolingual performance. Moreover, PRF was successful in raising the performance of transitive translation routes in absolute terms as well as in relation to monolingual and direct translation performance applying PRF.

A Word Game Support Tool Case Study

This article reports on the approach taken, experience gathered, and results found in building a tool to support the derivation of solutions to a particular kind of word game. This required that techniques had to be derived for simple yet acceptably quick access to a dictionary of natural language words (in the present case, Afrikaans). The main challenge was to access a large corpus of natural language words via a partial match retrieval technique. Other challenges included discovering how to represent such a dictionary in a "semi-compressed" format, thus arriving at a balance that favours search speed but nevertheless derives a savings on storage requirements. In addition, a query language had to be developed that would effectively exploit this access method. The system is designed to support a more intelligent query capability in the future. Acceptable response times were achieved even though an interpretive scripting language, ObjectREXX, was used. Cet article présente la méthode utilisée, l’expérience menée et les résultats obtenus dans le processus de construction d’un outil d'aide à la dérivation des solutions relatives à un type particulier de jeux de mots. Ceci requiert que des techniques soient dérivées pour un accès simple et rapide dans le dictionnaire des mots du langage naturel (l’Afrikaans pour le cas d’espèce). Le gros problème était d’accéder à un large corpus de mots du langage naturel à travers la technique d’identification de mots par extraction partielle. L’autre défi était de représenter un tel dictionnaire sous un format «semi-compressé», permettant ainsi de se trouver dans une situation qui améliore non seulement le temps de recherche dans le dictionnaire, mais aussi l’espace requis pour sa sauvegarde. De plus, un langage de requête, exploitant de façon effective la dite méthode d’accès devait être mise en oeuvre. Le système est conçu de façon à supporter dans le futur des requêtes plus intelligentes. Un temps de réponse acceptable a été obtenu bien qu'un langage interprétatif de Scripting (ObjREXX) ait été utilisé.