Howard Ho

IBM Research - Almaden

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Mauricio A. Hernández

IBM Research - Almaden

Lucian Popa

IBM Research - Almaden

Rajasekar Krishnamurthy

Western Michigan University

Shivakumar Vaithyanathan

IBM Research - Almaden

Ioana Stanoi

IBM (United States)

Huaiyu Zhu

Zhejiang University

Yunyao Li

University of Michigan–Ann Arbor

Georgia Koutrika

Athena Research and Innovation Center In Information Communication & Knowledge Technologies

Lucian Popa

IBM Research - Almaden

Yie W. Chien

Kaohsiung Medical University

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IBM (United States)

IBM Research - Almaden

University of Toronto

Microsoft (United States)

IBM Research - Thomas J. Watson Research Center

University of Miami

Google (United States)

University of California, Berkeley

University of Michigan–Ann Arbor

Universidad del Noreste

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Extracting, Linking and Integrating Data from Public Sources: A Financial Case Study.

IEEE Data(base) Engineering Bulletin (2011)

Douglas Burdick Mauricio A. Hernández Howard Ho Georgia Koutrika Rajasekar Krishnamurthy

We present Midas, a system that uses complex data processing to extract and aggregate facts from a large collection of structured and unstructured documents into a set of unified, clean entities and relationships. Midas focuses on data for financial companies and is based on periodic filings with the U.S. Securities and Exchange Commission (SEC) and Federal Deposit Insurance Corporation (FDIC). We show that, by using data aggregated by Midas, we can provide valuable insights about financial institutions either at the whole system level or at the individual company level. The key technology components that we implemented in Midas and that enable the various financial applications are: information extraction, entity resolution, mapping and fusion, all on top of a scalable infrastructure based on Hadoop. We describe our experience in building the Midas system and also outline the key research questions that remain to be addressed towards building a generic, high-level infrastructure for large-scale data integration from public sources.

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Citations (55)

StreamTX

Proceedings of the VLDB Endowment (2008)

Wook-Shin Han Haifeng Jiang Howard Ho Quanzhong Li

We study the problem of extracting flattened tuple data from streaming, hierarchical XML data. Tuple-extraction queries are essentially XML pattern queries with multiple extraction nodes. Their typical applications include mapping-based XML transformation and integrated (set-based) processing of XML and relational data. Holistic twig joins are known for the optimal matching of XML pattern queries on parsed/indexed XML data. Naïve application of the holistic twig joins to streaming XML data incurs unnecessary disk I/Os. We adapt the holistic twig joins for tuple-extraction queries on streaming XML with two novel features: first, we use the block-and-trigger technique to consume streaming XML data in a best-effort fashion without compromising the optimality of holistic matching; second, to reduce peak buffer sizes and overall running times, we apply query-path pruning and existential-match pruning techniques to aggressively filter irrelevant incoming data. We compare our solution with the direct competitor TurboXPath and other alternative approaches that use full-fledged query engines such as XQuery or XSLT engines for tuple extraction. The experiments using real-world XML data and queries demonstrated that our approach 1) outperformed its competitors by up to orders of magnitude, and 2) exhibited almost linear scalability. Our solution has been demonstrated extensively to IBM customers and will be included in customer engagement applications in healthcare.

XML Schema (W3C)

10.14778/1453856.1453891

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Citations (12)

Development of a new nicotine transdermal delivery system: in vitro kinetics studies and clinical pharmacokinetic evaluations in two ethnic groups

Journal of Controlled Release (1993)

Senshang Lin Howard Ho Yie W. Chien

10.1016/0168-3659(93)90185-8

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Citations (21)

Biomembrane Permeation of Nicotine: Mechanistic Studies with Porcine Mucosae and Skin

Journal of Pharmaceutical Sciences (1997)

Mona K. Nair Dushendra J. Chetty Yie W. Chien Howard Ho

10.1021/js960095w

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Citations (88)

Robust measurement of suspended sediment concentration based on the Tikhonov regulation and L-curve

EGUGA (2018)

Xingyu Chen Howard Ho Xudong Fu

Source

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Citations (0)

A hierarchical fuzzy logic controller with a velocity modifier for restructurable flight control systems

Guidance, Navigation, and Control Conference (1995)

Howard Ho M. Balakrishnan

10.2514/6.1995-3228

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Citations (3)

A Case Study Examining the Career Academy Model at a Large Urban Public High School.

ProQuest LLC eBooks (2013)

Howard Ho

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Citations (0)

Web Information Extraction

Encyclopedia of Database Systems (2018)

Laura Chiticariu Marina Danilevsky Howard Ho Rajasekar Krishnamurthy Yunyao Li

10.1007/978-1-4614-8265-9_459

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Citations (3)

Nested mappings: schema mapping reloaded

Ariel Fuxman Mauricio A. Hernández Howard Ho Renée J. Miller Paolo Papotti

Many problems in information integration rely on specifications, called schema mappings, that model the relationships between schemas. Schema mappings for both relational and nested data are well-known. In this work, we present a new formalism for schema mapping that extends these existing formalisms in two significant ways. First, our nested mappings allow for nesting and correlation of mappings. This results in a natural programming paradigm that often yields more accurate specifications. In particular, we show that nested mappings can naturally preserve correlations among data that existing mapping formalisms cannot. We also show that using nested mappings for purposes of exchanging data from a source to a target will result in less redundancy in the target data. The second extension to the mapping formalism is the ability to express, in a declarative way, grouping and data merging semantics. This semantics can be easily changed and customized to the integration task at hand. We present a new algorithm for the automatic generation of nested mappings from schema matchings (that is, simple element-to-element correspondences between schemas). We have implemented this algorithm, along with algorithms for the generation of transformation queries (e.g., XQuery) based on the nested mapping specification. We show that the generation algorithms scale well to large, highly nested schemas. We also show that using nested mappings in data exchange can drastically reduce the execution cost of producing a target instance, particularly over large data sources, and can also dramatically improve the quality of the generated data.

Data Exchange

Schema (genetic algorithms)

10.5555/1182635.1164135

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Citations (131)

Facilitating pattern discovery for relation extraction with semantic-signature-based clustering

Yunyao Li Vivian S. Chu Sebastian Blohm Huaiyu Zhu Howard Ho

Hand-crafted textual patterns have been the mainstay device of practical relation extraction for decades. However, there has been little work on reducing the manual effort involved in the discovery of effective textual patterns for relation extraction. In this paper, we propose a clustering-based approach to facilitate the pattern discovery for relation extraction. Specifically, we define the notion of semantic signature to represent the most salient features of a textual fragment. We then propose a novel clustering algorithm based on semantic signature, S2C, and its enhancement S2C+. Experiments on two real-world data sets show that, when compared with k-means clustering, S2C and S2C+ are at least an order of magnitude faster, while generating high quality clusters that are at least comparable to the best clusters generated by k-means without requiring any manual tuning. Finally, a user study confirms that our clustering-based approach can indeed help users discover effective textual patterns for relation extraction with only a fraction of the manual effort required by the conventional approach.

Relationship extraction

Signature (topology)

10.1145/2063576.2063781

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Citations (12)