Fast Search Engine Research Articles

Relative-phase simulated annealing for time-efficient and large-scale inverse design of achromatic thin lenses.

High-efficiency, broadband, wafer-size, and ultra-thin lenses are highly demanded, due to its great potential in abundant applications such as compact imaging modules. It is usually conceived that this target might be attainable given the advancement in nanofabrication, computation power and emerging algorithms, though challenging. Here, we reveal the inconvenient truth that for ultra-thin lenses, there actually exists intrinsic check-and-balance between size, broadband and performance. Unveiled by our inverse design algorithm, Relative-Phase Simulated Annealing (RPSA), focusing efficiency inevitably drops with refining wavelength intervals for better achromatic broadband features in optimized lens; and drops exponentially with increasing diameter and bandwidth, supported by our empirical formula. Meanwhile, with a slightly compromised goal, the powerfulness of RPSA is unlocked since it could provide a globally optimized design recipe whose time complexity relates to lens scale linearly rather than exponentially. This work, as a fast search engine for optimal solutions, paves the way towards practical large-scale achromatic ultra-thin lenses.

CRISPR-SE: a brute force search engine for CRISPR design.

CRISPR is a revolutionary genome-editing tool that has been broadly used and integrated within novel biotechnologies. A major component of existing CRISPR design tools is the search engines that find the off-targets up to a predefined number of mismatches. Many CRISPR design tools adapted sequence alignment tools as the search engines to speed up the process. These commonly used alignment tools include BLAST, BLAT, Bowtie, Bowtie2 and BWA. Alignment tools use heuristic algorithm to align large amount of sequences with high performance. However, due to the seed-and-extend algorithms implemented in the sequence alignment tools, these methods are likely to provide incomplete off-targets information for ultra-short sequences, such as 20-bp guide RNAs (gRNA). An incomplete list of off-targets sites may lead to erroneous CRISPR design. To address this problem, we derived four sets of gRNAs to evaluate the accuracy of existing search engines; further, we introduce a search engine, namely CRISPR-SE. CRISPR-SE is an accurate and fast search engine using a brute force approach. In CRISPR-SE, all gRNAs are virtually compared with query gRNA, therefore, the accuracies are guaranteed. We performed the accuracy benchmark with multiple search engines. The results show that as expected, alignment tools reported an incomplete and varied list of off-target sites. CRISPR-SE performs well in both accuracy and speed. CRISPR-SE will improve the quality of CRISPR design as an accurate high-performance search engine.

GEMINI: a computationally-efficient search engine for large gene expression datasets.

BackgroundLow-cost DNA sequencing allows organizations to accumulate massive amounts of genomic data and use that data to answer a diverse range of research questions. Presently, users must search for relevant genomic data using a keyword, accession number of meta-data tag. However, in this search paradigm the form of the query – a text-based string – is mismatched with the form of the target – a genomic profile.ResultsTo improve access to massive genomic data resources, we have developed a fast search engine, GEMINI, that uses a genomic profile as a query to search for similar genomic profiles. GEMINI implements a nearest-neighbor search algorithm using a vantage-point tree to store a database of n profiles and in certain circumstances achieves an mathcal {O}(log n) expected query time in the limit. We tested GEMINI on breast and ovarian cancer gene expression data from The Cancer Genome Atlas project and show that it achieves a query time that scales as the logarithm of the number of records in practice on genomic data. In a database with 105 samples, GEMINI identifies the nearest neighbor in 0.05 sec compared to a brute force search time of 0.6 sec.ConclusionsGEMINI is a fast search engine that uses a query genomic profile to search for similar profiles in a very large genomic database. It enables users to identify similar profiles independent of sample label, data origin or other meta-data information.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-0934-8) contains supplementary material, which is available to authorized users.

MDHT: a multi-level-indexed DHT algorithm to extra-large-scale data retrieval on HDFS/Hadoop architecture

Corresponding to the storing and fast searching needs of an extra-large scale of energy monitoring and statistics data, we propose a multi-level-indexed distributed hash table (mDHT) algorithm and complete a MapReduce implementation of the algorithm on the open-standard HDFS/Hbase platform. Such an approach uses a columnar storage structure for energy consumption data storage and creates a hashed index table to provide a quick search and retrieval method for extra-large-scale data processing systems. Such a hashed indexing scheme is implemented on a 3-node Hadoop cluster, and the simulation experiments at a scale up to 48 million data records indicate that, when the data volume reaches the scale of 12 million to 48 millions, the proposed mDHT algorithm presents an outstanding performance in data writing operation, compared to that of traditional SQL Server implementation. Even compared to the single-indexed DHT (sDHT) application, the mDHT solution outperforms by reducing the data retrieval time by 24.5---48.6 %. The multi-level-indexed DHT algorithm presented in this paper contributes a key technique to developing a fast search engine to the extra-large scale of data on the cloud storage architecture.

Multimedia Web searching trends

AbstractIn this paper we examine and compare multimedia Web searching by Excite and FAST search engine users in 2001. Findings include: (1) some differences between the Excite and FAST multimedia Web searches, (2) FAST users submit more multimedia queries but fewer audio‐related queries, (3) FAST users take more time with queries and sessions compared to Excite users, but spend less time on audio queries, and (4) Excite users submit longer and more complex queries than FAST users. As the Excite search engine is U.S. based and FAST search engine is Norwegian based, these differences suggest some difference in the Web search behavior of U.S. and European Web users.

Search engines and Web dynamics

In this paper we study several dimensions of Web dynamics in the context of large-scale Internet search engines. Both growth and update dynamics clearly represent big challenges for search engines. We show how the problems arise in all components of a reference search engine model. Furthermore, we use the FAST Search Engine architecture as a case study for showing some possible solutions for Web dynamics and search engines. The focus is to demonstrate solutions that work in practice for real systems. The service is running live at www.alltheweb.com and major portals worldwide with more than 30 million queries a day, about 700 million full-text documents, a crawl base of 1.8 billion documents, updated every 11 days, at a rate of 400 documents/second. We discuss future evolution of the Web, and some important issues for search engines will be scheduling and query execution as well as increasingly heterogeneous architectures to handle the dynamic Web.

Retrieval technology and the information explosion

Among a range of important technical issues facing by publishers for profit, the most urgent would seem to be that, while CD-ROM represents an established, proven source of revenue, the vast majority of investment is currently going into Internet and Web development, where evidence to date shows that revenue is scarce. Considers the question of how to generate Web revenues with reference to the briefing paper, A model approach, produced by Optosof, the specialist in Internet and CD-ROM retrieval solutions. The paper looks at the relationship between publishers’ existing business models, and the technology issues affecting their ability to establish the Web as a profitable source of revenue in the short term. Suggests that a logical strategy might be to put core content on CD-ROM, while supplementing it with Internet based access to topical and real time content. The key benchmark as far as performance is concerned will be to have a product built around a fast search engine that offers simultaneous search of multiple databases stored on one or more servers and where retrieval of data allows instant analysis and easy view, copy, export and print. Concludes with useful advice on implementing a successful strategy based on these requirements.

SITE FINDER: Search Engines

From the creators of Wired , this is a very fast search engine with an index of 53 million Web documents. PC Magazine [[HN1][1]] selected it as their number one choice for its advanced search features. Both the Web and Usenet groups can be searched, and the query syntax