Advanced Query Research Articles

Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review.

Objective: Machine learning classification has been the most important computational development in the last years to satisfy the primary need of clinicians for automatic early diagnosis and prognosis. Nowadays, Random Forest (RF) algorithm has been successfully applied for reducing high dimensional and multi-source data in many scientific realms. Our aim was to explore the state of the art of the application of RF on single and multi-modal neuroimaging data for the prediction of Alzheimer's disease.Methods: A systematic review following PRISMA guidelines was conducted on this field of study. In particular, we constructed an advanced query using boolean operators as follows: (“random forest” OR “random forests”) AND neuroimaging AND (“alzheimer's disease” OR alzheimer's OR alzheimer) AND (prediction OR classification). The query was then searched in four well-known scientific databases: Pubmed, Scopus, Google Scholar and Web of Science.Results: Twelve articles—published between the 2007 and 2017—have been included in this systematic review after a quantitative and qualitative selection. The lesson learnt from these works suggest that when RF was applied on multi-modal data for prediction of Alzheimer's disease (AD) conversion from the Mild Cognitive Impairment (MCI), it produces one of the best accuracies to date. Moreover, the RF has important advantages in terms of robustness to overfitting, ability to handle highly non-linear data, stability in the presence of outliers and opportunity for efficient parallel processing mainly when applied on multi-modality neuroimaging data, such as, MRI morphometric, diffusion tensor imaging, and PET images.Conclusions: We discussed the strengths of RF, considering also possible limitations and by encouraging further studies on the comparisons of this algorithm with other commonly used classification approaches, particularly in the early prediction of the progression from MCI to AD.

TS Corpus Project: An online Turkish Dictionary and TS DIY Corpus

TS Corpus is a free and independent project that aims building Turkish corpora, NLP tools and linguistic datasets. Since 2011, 10 corpora, various NLP tools, a large dataset and an online dictionary has been released. This paper focuses on the “online dictionary” and “ TS do-it-yourself corpus” released by the project. The dictionary data is based on TDK (Turkish Language Society) Contemporary Dictionary. However, the dictionary published serves many enhanced functions at user interface level. But, the main importance of the study is about the results presented to the users upon their queries; the presentation of collocations and tri-grams of the key word searched for. The collocations are harvested from a large Turkish corpus, +760 million tokens and the tri-grams were generated from Turkish Wikipedia pages. The do-it-yourself corpus (TS DIY Corpus), allows users to build their own corpora, modify or delete the uploaded texts and run queries. Users may run queries in different modes, such as “as is”, “starting/ending with” or including; besides advanced query option allows users to run queries with part-of-speech tags and lemmas. The results are given in KWIC (keyword in context) format. Various text classification options such as pubdate, author, domain, genre etc. could be selected during corpus creation. As the number of available Turkish corpora is limited, TS DIY Corpus is applicant to be a useful, well-known and largely used software for the scholars and researchers who wants to use a Turkish corpus or study over Turkish texts of their own.

Fractal: An advanced multidimensional range query lookup protocol on nested rings for distributed systems

One of the key issues in large-scale distributed systems such as P2P and grids is the capability of efficient multidimensional range query processing. Although several methods have recently been proposed for solving this problem on distributed systems, these methods have not been able to meet the fundamental necessity of a typical method on large-scale distributed systems, i.e., scalability.This paper presents Fractal, a fully decentralized and highly scalable multidimensional range query lookup protocol for distributed systems. In this work, to organize the available nodes in the system, an n-dimensional space called Key Space is utilized. The available nodes on the nested Fractal rings maintain information about only O(logN) other nodes, and the Fractal lookup protocol discovers the destination node through these nested rings with a logarithmic cost. Because of its flexibility, Fractal allows the system to create a concept called Layering, which minimizes the probability of the wide-area message transfers (WAMTs) during the lookup process. Using several criteria, Fractal is compared with several successful methods that have recently been presented. Simulation results show the efficiency and performance of Fractal in networks of different sizes.

Real-time social media retrieval with spatial, temporal and social constraints

Search in social network is continuously being expanded to enhance user experience. Besides basic textual retrieval, users can also search based on features such as spatial proximity, temporal freshness and/or social closeness. To efficiently process each advanced query type, customized indexing mechanisms have been developed. However, such mechanisms only perform well for the query types that they were designed for; moreover, they are not readily adaptable to support other query types. In this paper, we propose an interval-at-a-time (IAAT) framework as a first attempt to provide a one-size-fits-all solution to social media retrieval with spatial, temporal and social constraints. In addition, the algorithm relies on inverted index only, which makes it compatible with conventional search engines. The inverted lists are sorted by document id and the insertion is very fast because only append operation is involved. Experiments conducted on two large-scale Twitter datasets show that though IAAT is a unified strategy, it performs better than most of the state-of-the-art customized solutions in a variety of query types.

Evaluating Well-Formedness Constraints on Incomplete Models

In modern modeling tools used for model-driven development, the validation of several well-formedness constraints is continuously been carried out by exploiting advanced graph query engines to highlight conceptual design aws. However, while models are still under development, they are frequently par- tial and incomplete. Validating constraints on incomplete, partial models may identify a large number of irrelevant problems. By switching o the val- idation of these constraints, one may fail to reveal problematic cases which are dicult to correct when the model becomes suciently detailed. Here, we propose a novel validation technique for evaluating well-formed- ness constraints on incomplete, partial models with may and must semantics, e.g. a constraint without a valid match is satisable if there is a completion of the partial model that may satisfy it. To this end, we map the problem of constraint evaluation over partial models into regular graph pattern matching over complete models by semantically equivalent rewrites of graph queries.

Triage by ranking to support the curation of protein interactions.

Today, molecular biology databases are the cornerstone of knowledge sharing for life and health sciences. The curation and maintenance of these resources are labour intensive. Although text mining is gaining impetus among curators, its integration in curation workflow has not yet been widely adopted. The Swiss Institute of Bioinformatics Text Mining and CALIPHO groups joined forces to design a new curation support system named nextA5. In this report, we explore the integration of novel triage services to support the curation of two types of biological data: protein–protein interactions (PPIs) and post-translational modifications (PTMs). The recognition of PPIs and PTMs poses a special challenge, as it not only requires the identification of biological entities (proteins or residues), but also that of particular relationships (e.g. binding or position). These relationships cannot be described with onto-terminological descriptors such as the Gene Ontology for molecular functions, which makes the triage task more challenging. Prioritizing papers for these tasks thus requires the development of different approaches. In this report, we propose a new method to prioritize articles containing information specific to PPIs and PTMs. The new resources (RESTful APIs, semantically annotated MEDLINE library) enrich the neXtA5 platform. We tuned the article prioritization model on a set of 100 proteins previously annotated by the CALIPHO group. The effectiveness of the triage service was tested with a dataset of 200 annotated proteins. We defined two sets of descriptors to support automatic triage: the first set to enrich for papers with PPI data, and the second for PTMs. All occurrences of these descriptors were marked-up in MEDLINE and indexed, thus constituting a semantically annotated version of MEDLINE. These annotations were then used to estimate the relevance of a particular article with respect to the chosen annotation type. This relevance score was combined with a local vector-space search engine to generate a ranked list of PMIDs. We also evaluated a query refinement strategy, which adds specific keywords (such as ‘binds’ or ‘interacts’) to the original query. Compared to PubMed, the search effectiveness of the nextA5 triage service is improved by 190% for the prioritization of papers with PPIs information and by 260% for papers with PTMs information. Combining advanced retrieval and query refinement strategies with automatically enriched MEDLINE contents is effective to improve triage in complex curation tasks such as the curation of protein PPIs and PTMs. Database URL: http://candy.hesge.ch/nextA5

Informatization of Education: Pedagogical Services of the University Library

The article analyzes the problems of the modern libraries, which are characterized by the signi-ficant decline in attendance and search for new forms of the work with readers. There are described some methods to improve the user activity in public and University libraries; the greatest prospects are connected with the use of information technology. There are presented the classical information and library services, as well as the services based on the advanced query technology. It is stated that on the basis of this techno-logy there can be created a number of the unique services not only for academic and research activities, but for pedagogical work as well. There is proposed the technology of analyzing site traffic from the computers in reading rooms, as well as variations of implementation of pedagogical information and library services at the examples of actual problems of terrorism and drug addiction.

The antiSMASH database, a comprehensive database of microbial secondary metabolite biosynthetic gene clusters.

Secondary metabolites produced by microorganisms are the main source of bioactive compounds that are in use as antimicrobial and anticancer drugs, fungicides, herbicides and pesticides. In the last decade, the increasing availability of microbial genomes has established genome mining as a very important method for the identification of their biosynthetic gene clusters (BGCs). One of the most popular tools for this task is antiSMASH. However, so far, antiSMASH is limited to de novo computing results for user-submitted genomes and only partially connects these with BGCs from other organisms. Therefore, we developed the antiSMASH database, a simple but highly useful new resource to browse antiSMASH-annotated BGCs in the currently 3907 bacterial genomes in the database and perform advanced search queries combining multiple search criteria. antiSMASH-DB is available at http://antismash-db.secondarymetabolites.org/.

Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration.

Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies.

Dissecting the biological relationship between TCGA miRNA and mRNA sequencing data using MMiRNA-Viewer.

BackgroundMicroRNAs (miRNA) are short nucleotides that interact with their target genes through 3′ untranslated regions (UTRs). The Cancer Genome Atlas (TCGA) harbors an increasing amount of cancer genome data for both tumor and normal samples. However, there are few visualization tools focusing on concurrently displaying important relationships and attributes between miRNAs and mRNAs of both cancer tumor and normal samples. Moreover, a deep investigation of miRNA-mRNA target and biological relationships across multiple cancer types by integrating web-based analysis has not been thoroughly conducted.ResultsWe developed an interactive visualization tool called MMiRNA-Viewer that can concurrently present the co-relationships of expression between miRNA-mRNA pairs of both tumor and normal samples into a single graph. The input file of MMiRNA-Viewer contains the expression information including fold changes between normal and tumor samples for mRNAs and miRNAs, the correlation between mRNA and miRNA, and the predicted target relationship by a number of databases. Users can also load their own input data into MMiRNA-Viewer and visualize and compare detailed information about cancer-related gene expression changes, and also changes in the expression of transcription-regulating miRNAs.To validate the MMiRNA-Viewer, eight types of TCGA cancer datasets with both normal and control samples were selected in this study and three filter steps were applied subsequently. We performed Gene Ontology (GO) analysis for genes available in final selected 238 pairs and also for genes in the top 5 % (95 percentile) for each of eight cancer types to report a significant number of genes involved in various biological functions and pathways. We also calculated various centrality measurement matrices for the largest connected component(s) in each of eight cancers and reported top genes and miRNAs with high centrality measurements.ConclusionsWith its user-friendly interface, dynamic visualization and advanced queries, we also believe MMiRNA-Viewer offers an intuitive approach for visualizing and elucidating co-relationships between miRNAs and mRNAs of both tumor and normal samples. We suggest that miRNA and mRNA pairs with opposite fold changes of their expression and with inverted correlation values between tumor and normal samples might be most relevant for explaining the decoupling of mRNAs and their targeting miRNAs in tumor samples for certain cancer types.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1219-y) contains supplementary material, which is available to authorized users.

EpiGeNet: A Graph Database of Interdependencies Between Genetic and Epigenetic Events in Colorectal Cancer.

The development of colorectal cancer (CRC)-the third most common cancer type-has been associated with deregulations of cellular mechanisms stimulated by both genetic and epigenetic events. StatEpigen is a manually curated and annotated database, containing information on interdependencies between genetic and epigenetic signals, and specialized currently for CRC research. Although StatEpigen provides a well-developed graphical user interface for information retrieval, advanced queries involving associations between multiple concepts can benefit from more detailed graph representation of the integrated data. This can be achieved by using a graph database (NoSQL) approach. Data were extracted from StatEpigen and imported to our newly developed EpiGeNet, a graph database for storage and querying of conditional relationships between molecular (genetic and epigenetic) events observed at different stages of colorectal oncogenesis. We illustrate the enhanced capability of EpiGeNet for exploration of different queries related to colorectal tumor progression; specifically, we demonstrate the query process for (i) stage-specific molecular events, (ii) most frequently observed genetic and epigenetic interdependencies in colon adenoma, and (iii) paths connecting key genes reported in CRC and associated events. The EpiGeNet framework offers improved capability for management and visualization of data on molecular events specific to CRC initiation and progression.

An ICT-Based Platform to Monitor Protocols in the Healthcare Environment.

Procedures from the healthcare domain involve highly critical actions as they may pose a risk for patients' life. Therefore, a large effort is devoted to the standardization in clinical praxis and to the control of quality for these protocols in order to minimize hazards. In this line, this work is compelled to provide an ICT-based support to carry out these controls in a simple and effective manner. Using a methodology based on HACCP and taking advantage of Semantic tools, a holistic platform of services for traceability and control of processes has been designed and implemented. The applied paradigm is based on the use of Control Points as singular points to generate traces using observations and measures relevant for the processes considered. Based on those, it is possible to offer services for advanced querying and knowledge inference. The local deployment just requires regular mobile phones or tablets making this solution cost-effective and easily replicable.

Kodiak

Turn's online advertising campaigns produce petabytes of data. This data is composed of trillions of events, e.g. impressions, clicks, etc., spanning multiple years. In addition to a timestamp, each event includes hundreds of fields describing the user's attributes, campaign's attributes, attributes of where the ad was served, etc. Advertisers need advanced analytics to monitor their running campaigns' performance, as well as to optimize future campaigns. This involves slicing and dicing the data over tens of dimensions over arbitrary time ranges. Many of these queries need to power the web portal to provide reports and dashboards. For an interactive response time, they have to have tens of milliseconds latency. At Turn's scale of operations, no existing system was able to deliver this performance in a cost effective manner. Kodiak, a distributed analytical data platform for web-scale high-dimensional data, was built to serve this need. It relies on pre-computations to materialize thousands of views to serve these advanced queries. These views are partitioned and replicated across Kodiak's storage nodes for scalability and reliability. They are system maintained as new events arrive. At query time, the system auto-selects the most suitable view to serve each query. Kodiak has been used in production for over a year. It hosts 2490 views for over three petabytes of raw data serving over 200K queries daily. It has median and 99% query latencies of 8 ms and 252 ms respectively. Our experiments show that its query latency is 3 orders of magnitude faster than leading big data platforms on head-to-head comparisons using Turn's query workload. Moreover, Kodiak uses 4 orders of magnitude less resources to run the same workload.

Efficient monochromatic and bichromatic probabilistic reverse top-k query processing for uncertain big data

There has been an increasing growth in numerous applications that naturally generate large volumes of uncertain data. By the advent of such applications, the support of advanced analysis query processing such as the top-k and reverse top-k for uncertain big data has become important. In this paper, we model firstly probabilistic reverse top-k queries over uncertain big data for the discrete situation, in both monochromatic and bichromatic cases, denoted by MPRT and BPRT queries, respectively. We determine the partitions of solution space of MPRT queries and provide in theory a mathematical model for solving arbitrary dimensional data space. Additionally, we propose effective pruning heuristics to reduce the search space of BPRT queries. Moreover, efficient query procedures are presented seamlessly with integration of the proposed pruning strategies. Extensive experiments demonstrate the efficiency and effectiveness of our proposed approaches with various experimental settings.

Quantifying the Connectivity of a Semantic Warehouse and Understanding its Evolution over Time

In many applications one has to fetch and assemble pieces of information coming from more than one source for building a semantic warehouse offering more advanced query capabilities. In this paper the authors describe the corresponding requirements and challenges, and they focus on the aspects of quality and value of the warehouse. For this reason they introduce various metrics (or measures) for quantifying its connectivity, and consequently its ability to answer complex queries. The authors demonstrate the behaviour of these metrics in the context of a real and operational semantic warehouse, as well as on synthetically produced warehouses. The proposed metrics allow someone to get an overview of the contribution (to the warehouse) of each source and to quantify the value of the entire warehouse. Consequently, these metrics can be used for advancing data/endpoint profiling and for this reason the authors use an extension of VoID (for making them publishable). Such descriptions can be exploited for dataset/endpoint selection in the context of federated search. In addition, the authors show how the metrics can be used for monitoring a semantic warehouse after each reconstruction reducing thereby the cost of quality checking, as well as for understanding its evolution over time.

A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations

Abstract Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.

Design and development of semantic web-based system for computer science domain-specific information retrieval

Summary In semantic web-based system, the concept of ontology is used to search results by contextual meaning of input query instead of keyword matching. From the research literature, there seems to be a need for a tool which can provide an easy interface for complex queries in natural language that can retrieve the domain-specific information from the ontology. This research paper proposes an IRSCSD system (Information retrieval system for computer science domain) as a solution. This system offers advanced querying and browsing of structured data with search results automatically aggregated and rendered directly in a consistent user-interface, thus reducing the manual effort of users. So, the main objective of this research is design and development of semantic web-based system for integrating ontology towards domain-specific retrieval support. Methodology followed is a piecemeal research which involves the following stages. First Stage involves the designing of framework for semantic web-based system. Second stage builds the prototype for the framework using Protege tool. Third Stage deals with the natural language query conversion into SPARQL query language using Python-based QUEPY framework. Fourth Stage involves firing of converted SPARQL queries to the ontology through Apache's Jena API to fetch the results. Lastly, evaluation of the prototype has been done in order to ensure its efficiency and usability. Thus, this research paper throws light on framework development for semantic web-based system that assists in efficient retrieval of domain-specific information, natural language query interpretation into semantic web language, creation of domain-specific ontology and its mapping with related ontology. This research paper also provides approaches and metrics for ontology evaluation on prototype ontology developed to study the performance based on accessibility of required domain-related information.

Methods to Enhance Transformation in Near Real Time ETL

During the transformation phase of near real time ETL there could be some technique applied so that we get better results in terms of speed and accuracy. Transformation phase concentrates on changing the transactional data into semantically suitable format for the data warehouse. We try to bring in some of the solution during transformation phase that could enhance the speed and accuracy of the phase like advanced query optimization techniques, designing a new workflow so that we could reschedule some of the task. E.g. some functions applied on two parallel flows could be applied only once if the flows are converging. Also we look into some of the solutions for stream data how we could merge stream data and stored data, the challenges like speed and memory utilization. We also explore solutions like event based transformation for selected items, and handling of metadata efficiently so that it could add valued to the transformation phase.

W-tree

World Wide Web applications need to use, constantly update, and maintain large webgraphs for executing several tasks, such as calculating the web impact factor, finding hubs and authorities, performing link analysis by webometrics tools, and ranking webpages by web search engines. Such webgraphs need to use a large amount of main memory, and, frequently, they do not completely fit in, even if compressed. Therefore, applications require the use of external memory. This article presents a new compact representation for webgraphs, called w-tree , which is designed specifically for external memory. It supports the execution of basic queries (e.g., full read, random read, and batch random read), set-oriented queries (e.g., superset, subset, equality, overlap, range, inlink, and co-inlink), and some advanced queries, such as edge reciprocal and hub and authority. Furthermore, a new layout tree designed specifically for webgraphs is also proposed, reducing the overall storage cost and allowing the random read query to be performed with an asymptotically faster runtime in the worst case. To validate the advantages of the w-tree, a series of experiments are performed to assess an implementation of the w-tree comparing it to a compact main memory representation. The results obtained show that w-tree is competitive in compression time and rate and in query time, which may execute several orders of magnitude faster for set-oriented queries than its competitors. The results provide empirical evidence that it is feasible to use a compact external memory representation for webgraphs in real applications, contradicting the previous assumptions made by several researchers.

SAFQuery: a simple and flexible advanced Web search interface

Purpose This paper aims to introduce a prototype system called SAFQuery (Simple And Flexible Query interface). In many existing Web search interfaces, simple and advanced query processes are treated separately that cannot be issued interchangeably. In addition, after several rounds of queries for specific information need(s), it is possible that users might wish to re-examine the retrieval results corresponding to some previous queries or to slightly modify some of the specific queries issued before. However, it is often hard to remember what queries have been issued. These factors make the current Web search process not very simple or flexible. Design/methodology/approach In SAFQuery, the simple and advanced query strategies are integrated into a single interface, which can easily formulate query specifications when needed in the same interface. Moreover, query history information is provided that displays the past query specifications, which can help with the memory load. Findings The authors' experiments by user evaluation show that most users had a positive experience when using SAFQuery. Specifically, it is easy to use and can simplify the Web search task. Originality/value The proposed prototype system provides simple and flexible Web search strategies. Particularly, it allows users to easily issue simple and advanced queries based on one single query interface, interchangeably. In addition, users can easily input previously issued queries without spending time to recall what the queries are and/or to re-type previous queries.