Document replication strategies for geographically distributed web search engines

Cataloged from PDF version of article.Large-scale web search engines are composed of multiple data centers that are geographically distant to each other. Typically, a user query is processed in a data center that is geographically close to the origin of the query, over a replica of the entire web index. Compared to a centralized, single-center search engine, this architecture offers lower query response times as the network latencies between the users and data centers are reduced. However, it does not scale well with increasing index sizes and query traffic volumes because queries are evaluated on the entire web index, which has to be replicated and maintained in all data centers. As a remedy to this scalability problem, we propose a document replication framework in which documents are selectively replicated on data centers based on regional user interests. Within this framework, we propose three different document replication strategies, each optimizing a different objective: reducing the potential search quality loss, the average query response time, or the total query workload of the search system. For all three strategies, we consider two alternative types of capacity constraints on index sizes of data centers. Moreover, we investigate the performance impact of query forwarding and result caching. We evaluate our strategies via detailed simulations, using a large query log and a document collection obtained from the Yahoo! web search engine. (C) 2012 Elsevier Ltd. All rights reserved

Exploiting the Bipartite Structure of Entity Grids for Document Coherence and Retrieval

International audienceDocument coherence describes how much sense text makes in terms of its logical organisation and discourse flow. Even though coherence is a relatively difficult notion to quantify precisely, it can be approximated automatically. This type of coherence modelling is not only interesting in itself, but also useful for a number of other text processing tasks, including Information Retrieval (IR), where adjusting the ranking of documents according to both their relevance and their coherence has been shown to increase retrieval effectiveness.The state of the art in unsupervised coherence modelling represents documents as bipartite graphs of sentences and discourse entities, and then projects these bipartite graphs into one–mode undirected graphs. However, one–mode projections may incur significant loss of the information present in the original bipartite structure. To address this we present three novel graph metrics that compute document coherence on the original bipartite graph of sentences and entities. Evaluation on standard settings shows that: (i) one of our coherence metrics beats the state of the art in terms of coherence accuracy; and (ii) all three of our coherence metrics improve retrieval effectiveness because, as closer analysis reveals, they capture aspects of document quality that go undetected by both keyword-based standard ranking and by spam filtering. This work contributes document coherence metrics that are theoretically principled, parameter-free, and useful to IR

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

A Term-Based Inverted Index Partitioning Model for Efficient Distributed Query Processing

Cataloged from PDF version of article.In a shared-nothing, distributed text retrieval system, queries are processed over an inverted index that is partitioned among a number of index servers. In practice, the index is either document-based or term-based partitioned. This choice is made depending on the properties of the underlying hardware infrastructure, query traffic distribution, and some performance and availability constraints. In query processing on retrieval systems that adopt a term-based index partitioning strategy, the high communication overhead due to the transfer of large amounts of data from the index servers forms a major performance bottleneck, deteriorating the scalability of the entire distributed retrieval system. In this work, to alleviate this problem, we propose a novel inverted index partitioning model that relies on hypergraph partitioning. In the proposed model, concurrently accessed index entries are assigned to the same index servers, based on the inverted index access patterns extracted from the past query logs. The model aims to minimize the communication overhead that will be incurred by future queries while maintaining the computational load balance among the index servers. We evaluate the performance of the proposed model through extensive experiments using a real-life text collection and a search query sample. Our results show that considerable performance gains can be achieved relative to the term-based index partitioning strategies previously proposed in literature. In most cases, however, the performance remains inferior to that attained by document-based partitioning

A multi-level hypergraph partitioning algorithm using rough set clustering

The hypergraph partitioning problem has many applications in scientific computing and provides a more accurate inter-processor communication model for distributed systems than the equivalent graph problem. In this paper, we propose a sequential multi-level hypergraph partitioning algorithm. The algorithm makes novel use of the technique of rough set clustering in categorising the vertices of the hypergraph. The algorithm treats hyperedges as features of the hypergraph and tries to discard unimportant hyperedges to make better clustering decisions. It also focuses on the trade-off to be made between local vertex matching decisions (which have low cost in terms of the space required and time taken) and global decisions (which can be of better quality but have greater costs). The algorithm is evaluated and compared to state-of-the-art algorithms on a range of benchmarks. The results show that it generates better partition quality

The clinical features, diagnosis, treatment, and prognosis of neuroinvasive listeriosis: a multinational study

The aim of this study was to determine the independent risk factors, morbidity, and mortality of central nervous system (CNS) infections caused by Listeria monocytogenes. We retrospectively evaluated 100 episodes of neuroinvasive listeriosis in a multinational study in 21 tertiary care hospitals of Turkey, France, and Italy from 1990 to 2014. The mean age of the patients was 57 years (range, 19-92 years), and 64% were males. The all-cause immunosuppression rate was 54 % (54/100). Forty-nine (49 %) patients were referred to a hospital because of the classical triad of symptoms (fever, nuchal rigidity, and altered level of consciousness). Rhombencephalitis was detected radiologically in 9 (9 %) cases. Twenty-seven (64 %) of the patients who had cranial magnetic resonance imaging (MRI) performed had findings of meningeal and parenchymal involvement. The mean delay in the initiation of specific treatment was 6.8 +/- 7 days. Empiric treatment was appropriate in 52 (52 %) patients. The mortality rate was 25 %, while neurologic sequelae occurred in 13 % of the patients. In the multivariate analysis, delay in treatment [odds ratio (OR), 1.07 [95 % confidence interval (CI), 1.01-1.16]] and seizures (OR, 3.41 [95 % CI, 1.05-11.09]) were significantly associated with mortality. Independent risk factors for neurologic sequelae were delay in treatment (OR, 1.07 [95 % CI, 1.006-1.367]) and presence of bacteremia (OR, 45.2 [95 % CI, 2.73-748.1]). Delay in the initiation of treatment of neuroinvasive listeriosis was a poor risk factor for unfavorable outcomes. Bacteremia was one of the independent risk factors for morbidity, while the presence of seizures predicted worse prognosis. Moreover, the addition of aminoglycosides to ampicillin monotherapy did not improve patients' prognosis

Temporal Trends in the Epidemiology of HIV in Turkey

Objective: The aim of this study was to analyze the temporal trends of HIV epidemiology in Turkey from 2011 to 2016.Methods: Thirty-four teams from 28 centers at 17 different cities participated in this retrospective study. Participating centers were asked to complete a structured form containing questions about epidemiologic, demographic and clinical characteristics of patients presented with new HIV diagnosis between 2011 and 2016. Demographic data from all centers (complete or partial) were included in the analyses. For the cascade of care analysis, 15 centers that provided full data from 2011 to 2016 were included. Overall and annual distributions of the data were calculated as percentages and the Chi square test was used to determine temporal changes.Results: A total of 2,953 patients between 2011 and 2016 were included. Overall male to female ratio was 5:1 with a significant increase in the number of male cases from 2011 to 2016 (p500 cells/mm(3) while 46.7% presented with a CD4 T cell count of <350 cells/mm(3). Among newly diagnosed cases, 79% were retained in care, and all such cases initiated ART with 73% achieving viral suppression after six months of antiretroviral therapy.Conclusion: The epidemiologic profile of HIV infected individuals is changing rapidly in Turkey with an increasing trend in the number of newly diagnosed people disclosing themselves as MSM. New diagnoses were mostly at a young age. The late diagnosis was found to be a challenging issue. Despite the unavailability of data for the first 90, Turkey is close to the last two steps of 90-90-90 targets.C1 [Erdinc, F. S.; Hatipoglu, C. A.] Ankara Numune Training & Res Hosp, Infect Dis & Clin Microbiol, Ankara, Turkey.[Dokuzoguz, B.; Inkaya, A. C.] Ankara Numune Training & Researh Hosp, Infect Dis & Clin Microbiol, Ankara, Turkey.[Unal, S.] Hacettepe Univ Hastaneleri, Dept Infect Dis & Clin Microbiol, Ankara, Turkey.[Komur, S.] Cukurova Univ, Dept Infect Dis & Clin Microbiol, Adana, Turkey.[Inan, D.] Akdeniz Univ, Dept Infect Dis & Clin Microbiol, Antalya, Turkey.[Karaoglan, I] Gaziantep Univ, Dept Infect Dis & Clin Microbiol, Gaziantep, Turkey.[Deveci, A.] Ondokuz Mayis Univ, Dept Infect Dis & Clin Microbiol, Samsun, Turkey.[Celen, M. K.] Dicle Univ, Dept Infect Dis & Clin Microbiol, Diyarbakir, Turkey.[Kose, S.] Izmir Tepecik Training & Res Hosp, Dept Infect Dis & Clin Microbiol, Izmir, Turkey.[Erben, N.] Eskisehir Osmangazi Univ, Dept Infect Dis & Clin Microbiol, Fac Med, Eskisehir, Turkey.[Senturk, G. C.] Diskapi Yildirim Beyazit Training & Res Hosp, Dept Infect Dis & Clin Microbiol, Ankara, Turkey.[Heper, Y.; Yilmaz, E.; Kazak, E.] Uludag Univ, Dept Infect Dis & Clin Microbiol, Bursa, Turkey.[Kutlu, S. S.] Pamukkale Univ, Dept Infect Dis & Clin Microbiol, Denizli, Turkey.[Sumer, S.] Selcuk Univ, Dept Infect Dis & Clin Microbiol, Konya, Turkey.[Kandemir, B.] Necmettin Erbakan Univ, Meram Med Fac Hosp, Dept Infect Dis & Clin Microbiol, Konya, Turkey.[Sirmatel, F.] Abant Izzet Baysal Univ, Dept Infect Dis & Clin Microbiol, Bolu, Turkey.[Bayindir, Y.; Ersoy, Y.; Yetkin, F.] Inonu Univ, Dept Infect Dis & Clin Microbiol, Malatya, Turkey.[Yildirmak, M. T.] Okmeydani Training & Res Hosp, Dept Infect Dis & Clin Microbiol, Istanbul, Turkey.[Kayaaslan, B.] Yildirim Beyazit Univ, Dept Infect Dis & Clin Microbiol, Fac Med, Ankara, Turkey.[Ozden, K.] Ataturk Univ, Dept Infect Dis & Clin Microbiol, Erzurum, Turkey.[Sener, A.] Canakkale Onsekiz Mart Univ, Dept Infect Dis & Clin Microbiol, Canakkale, Turkey.[Kara, A.] Hacettepe Univ, Dept Infect Dis, Ihsan Dogramaci Childrens Hosp, Ankara, Turkey.[Gunal, O.] Samsun Training & Res Hosp, Dept Infect Dis & Clin Microbiol, Samsun, Turkey.[Birengel, S.] Ankara Univ, Dept Infect Dis & Clin Microbiol, Fac Med, Ankara, Turkey.[Akbulut, A.] Firat Univ, Dept Infect Dis & Clin Microbiol, Elazig, Turkey.[Cuvalci, N. O.] Antalya Training & Res Hosp, Dept Infect Dis & Clin Microbiol, Antalya, Turkey.[Sargin, F.] Medeniyet Univ, Dept Infect Dis & Clin Microbiol, Goztepe Training & Res Hosp, Istanbul, Turkey.[Pullukcu, H.; Gokengin, D.] Ege Univ, Dept Infect Dis & Clin Microbiol, Izmir, Turkey