Frank Schilder

Thomson Reuters, New York City, New York, United States

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Publications (44)0.66 Total impact

  • Blake Howald, Ravi Kondadadi, Frank Schilder
    The 10th International Conference on Computational Semantics; 03/2013
  • Frank Schilder, Ravi Kondadadi, Yana Kadiyska
    CICLING; 03/2012
  • Frank Schilder
    Computational Linguistics. 01/2010; 36:151-156.
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    Jochen L. Leidner, Frank Schilder
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    ABSTRACT: In the business world, analyzing and dealing with risk permeates all decisions and actions. However, to date, risk identification, the first step in the risk management cycle, has always been a manual activity with little to no intelligent software tool support. In addition, although companies are required to list risks to their business in their annual SEC filings in the USA, these descriptions are often very high-level and vague. In this paper, we introduce Risk Mining, which is the task of identifying a set of risks pertaining to a business area or entity. We argue that by combining Web mining and Information Extraction (IE) techniques, risks can be detected automatically before they materialize, thus providing valuable business intelligence. We describe a system that induces a risk taxonomy with concrete risks (e.g., interest rate changes) at its leaves and more abstract risks (e.g., financial risks) closer to its root node. The taxonomy is induced via a bootstrapping algorithms starting with a few seeds. The risk taxonomy is used by the system as input to a risk monitor that matches risk mentions in financial documents to the abstract risk types, thus bridging a lexical gap. Our system is able to automatically generate company specific "risk maps", which we demonstrate for a corpus of earnings report conference calls.
    ACL 2010, Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, July 11-16, 2010, Uppsala, Sweden, System Demonstrations; 01/2010
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    ABSTRACT: We present the first report of automatic sentiment summarization in the legal domain. This work is based on processing a set of legal questions with a system consisting of a semi-automatic Web blog search module and FastSum, a fully automatic extractive multi-document sentiment summarization system. We provide quantitative evaluation results of the summaries using legal expert reviewers. We report baseline evaluation results for query-based sentiment summarization for legal blogs: on a five-point scale, average responsiveness and linguistic quality are slightly higher than 2 (with human inter-rater agreement at k = 0.75). To the best of our knowledge, this is the first evaluation of sentiment summarization in the legal blogosphere.
    The 12th International Conference on Artificial Intelligence and Law, Proceedings of the Conference, June 8-12, 2009, Barcelona, Spain; 01/2009
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    ABSTRACT: TempEval is a framework for evaluating systems that automatically annotate texts with temporal relations. It was created in the context of the SemEval 2007 workshop and uses the TimeML annotation language. The evaluation consists of three subtasks of temporal annotation: anchoring an event to a time expression in the same sentence, anchoring an event to the document creation time, and ordering main events in consecutive sentences. In this paper we describe the TempEval task and the systems that participated in the evaluation. In addition, we describe how further task decomposition can bring even more structure to the evaluation of temporal relations.
    Language Resources and Evaluation 01/2009; 43:161-179. · 0.66 Impact Factor
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    Frank Schilder, Ravi Kondadadi
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    ABSTRACT: This paper introduces a new metric for automatically evaluation summaries called ContextChain. Based on an in-depth analysis of the TAC 2008 update summarization results, we show that previous automatic metrics such as ROUGE-2 and BE cannot reliably predict strong performing systems. We introduce two new terms called Correlation Recall and Correlation Precision and discuss how they cast more light on the coverage and the correctness of the respective metric. Our newly proposed metric called ContextChain incorporates findings from Giannakopoulos et al. (2008) and Barzilay and Lapata (2008) [2]. We show that our metric correlates with responsiveness scores even for the top n systems that participated in the TAC 2008 update summarization task, whereas ROUGE-2 and BE do not show a correlation for the top 25 systems.
    Proceedings of the 3rd IEEE International Conference on Semantic Computing (ICSC 2009), 14-16 September 2009, Berkeley, CA, USA; 01/2009
  • Text Analysis Conference (TAC); 01/2009
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    ABSTRACT: Multi-document summarization saves time when dealing with large document quantities, but state of the art only handles fact summarization. What about sentiment (attitudes held by somebody about something)? The solution to this problem is query-based sentiment summarization, a form of (multi-document) summarization, whereby the query specifies the polarity of interest that informs the summarizer. In this work, we describe our methods for performing polarity filtering for sentiment summarization.
    First Text Analysis Conference (TAC08), Gaithersburg, MD; 11/2008
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    ABSTRACT: In TAC 2008 we participated in the main task (Update Summarization) as well as the Senti-ment Summarization pilot task. We modified the FastSum system (Schilder and Kondadadi, 2008) and added more aggressive filtering in order to adapt the system to update summa-rization and sentiment summarization. For the Update Summarization task, we show that a classifier that identifies sentences that are sim-ilar to typical first sentences of a news article improves the overall linguistic quality of the generated summaries. For the Sentiment Sum-marization pilot task, we use a simple senti-ment classifier based on a gazetteer of positive and negative sentiment words derived from the General Inquirer and other sources to produce opinion-based summaries for a collection of blog posts given a set of positive and negative questions.
    TAC; 10/2008
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    Frank Schilder, Ravikumar Kondadadi
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    ABSTRACT: We present a fast query-based multi-document summarizer called FastSum based solely on word-frequency features of clusters, documents and topics. Summary sentences are ranked by a regression SVM. The summarizer does not use any expensive NLP techniques such as parsing, tagging of names or even part of speech information. Still, the achieved accuracy is comparable to the best systems presented in recent academic competitions (i.e., Document Understanding Conference (DUC)). Because of a detailed feature analysis using Least Angle Regression (LARS), FastSum can rely on a minimal set of features leading to fast processing times: 1250 news documents in 60 seconds.
    ACL 2008, Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics, June 15-20, 2008, Columbus, Ohio, USA, Short Papers; 01/2008
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    ABSTRACT: Opinion mining techniques add another dimension to search and summarization technology by actually identifying the author's opinion about a subject, rather than simply identifying the subject itself. Given the dramatic explosion of the blogosphere, both in terms of its data and its participants, it is becoming increasingly important to be able to measure the authority of these participants, especially when professional application areas are involved. After having performed preliminary investigations into sentiment analysis in the legal blogosphere, we are beginning a new direction of work which addresses representing, measuring, and monitoring the degree of authority and thus presumed credibility associated with various types of blog participants. In particular, we explore the utility of authority-detection layered atop opinion mining in the legal and financial domains.
    Proceedings of the 2nd ACM Workshop on Information Credibility on the Web, WICOW 2008, Napa Valley, California, USA, October 30, 2008; 01/2008
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    Jack G. Conrad, Frank Schilder
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    ABSTRACT: We perform a survey into the scope and utility of opinion mining in legal Weblogs (a.k.a. blawgs). The number of 'blogs' in the legal domain is growing at a rapid pace and many potential applications for opinion detection and monitoring are arising as a result. We summarize current approaches to opinion mining before describing different categories of blawgs and their potential impact on the law and the legal profession. In addition to educating the community on recent developments in the legal blog space, we also conduct some introductory opinion mining trials. We first construct a Weblog test collection containing blog entries that discuss legal search tools. We subsequently examine the performance of a language modeling approach deployed for both subjectivity analysis (i.e., is the text subjective or objective?) and polarity analysis (i.e., is the text affirmative or negative towards its subject?). This work may thus help establish early baselines for these core opinion mining tasks.
    The Eleventh International Conference on Artificial Intelligence and Law, Proceedings of the Conference, June 4-8, 2007, Stanford Law School, Stanford, California, USA; 01/2007
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    ABSTRACT: The TempEval task proposes a simple way to evaluate automatic extraction of temporal relations. It avoids the pitfalls of evaluat-ing a graph of inter-related labels by defin-ing three sub tasks that allow pairwise eval-uation of temporal relations. The task not only allows straightforward evaluation, it also avoids the complexities of full tempo-ral parsing.
    01/2007;
  • Frank Schilder, Graham Katz, James Pustejovsky
    01/2007;
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    Frank Schilder, Graham Katz, James Pustejovsky
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    ABSTRACT: The main focus of the Dagstuhl seminar 05151 was on TimeML-based temporal annotation and reasoning. We were concerned with three main points: how effectively can one use the TimeML language for consistent annotation, determining how useful such annotation is for further processing, and determining what modifications should be applied to the standard to make it more useful for applications such as question-answering and information retrieval.
    Annotating, Extracting and Reasoning about Time and Events, International Seminar, Dagstuhl Castle, Germany, April 10-15, 2005. Revised Papers; 01/2005
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    Graham Katz, James Pustejovsky, Frank Schilder
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    ABSTRACT: From 10.04.05 to 15.04.05, the Dagstuhl Seminar 05151 ``Annotating, Extracting and Reasoning about Time and Events'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available. @InProceedings{katz_et_al:DSP:2005:353, author = {Graham Katz and James Pustejovsky and Frank Schilder}, title = {05151 Abstracts Collection -- Annotating, Extracting and Reasoning about Time and Events}, booktitle = {Annotating, Extracting and Reasoning about Time and Events}, year = {2005}, editor = {Graham Katz and James Pustejovsky and Frank Schilder}, number = {05151}, series = {Dagstuhl Seminar Proceedings}, ISSN = {1862-4405}, publisher = {Internationales Begegnungs- und Forschungszentrum f{"u}r Informatik (IBFI), Schloss Dagstuhl, Germany}, address = {Dagstuhl, Germany}, URL = {http://drops.dagstuhl.de/opus/volltexte/2005/353}, annote = {Keywords: Text annotation, information extraction and retrieval, summarization, question answering, temporal reasoning} }
    01/2005;
  • Frank Schilder
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    ABSTRACT: This paper presents a prototype system that extracts events from the United States Code on U.S. immigration nationality and links these events to temporal constraints, such as in entered the United States before December 31, 2005. In addition, the paper provides an overview of what kinds of other temporal information can be found in different types of legal documents. In particular, it discusses how one could do further reasoning with the extracted temporal information for case law and statutes.
    Annotating, Extracting and Reasoning about Time and Events, International Seminar, Dagstuhl Castle, Germany, April 10-15, 2005. Revised Papers; 01/2005
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    Frank Schilder, Andrew McCulloh
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    ABSTRACT: The aim of this paper is to analyze what kinds of temporal information can be found in different types of legal documents. In particular, it provides a comparison of different legal document types (case law, statute or transactional document) andit discusses how one can do further reasoning with the extracted temporal information. @InProceedings{schilder_et_al:DSP:2005:313, author = {Frank Schilder and Andrew McCulloh}, title = {Temporal information extraction from legal documents}, booktitle = {Annotating, Extracting and Reasoning about Time and Events}, year = {2005}, editor = {Graham Katz and James Pustejovsky and Frank Schilder}, number = {05151}, series = {Dagstuhl Seminar Proceedings}, ISSN = {1862-4405}, publisher = {Internationales Begegnungs- und Forschungszentrum f{"u}r Informatik (IBFI), Schloss Dagstuhl, Germany}, address = {Dagstuhl, Germany}, URL = {http://drops.dagstuhl.de/opus/volltexte/2005/313}, annote = {Keywords: Extraction of temporal information, temporal reasoning, legal documents} }
    01/2005;
  • Source
    Graham Katz, James Pustejovsky, Frank Schilder
    [Show abstract] [Hide abstract]
    ABSTRACT: The main focus of the seminar was on TimeML-based temporal annotation and reasoning. We were concerned with three main points: determining how effectively one can use the TimeML language for consistent annotation, determining how useful such annotation is for further processing, and determining what modifications should be applied to the standard to improve its usefulness in applications such as question-answering and information retrieval. @InProceedings{katz_et_al:DSP:2005:354, author = {Graham Katz and James Pustejovsky and Frank Schilder}, title = {05151 Summary -- Annotating, Extracting and Reasoning about Time and Events}, booktitle = {Annotating, Extracting and Reasoning about Time and Events}, year = {2005}, editor = {Graham Katz and James Pustejovsky and Frank Schilder}, number = {05151}, series = {Dagstuhl Seminar Proceedings}, ISSN = {1862-4405}, publisher = {Internationales Begegnungs- und Forschungszentrum f{"u}r Informatik (IBFI), Schloss Dagstuhl, Germany}, address = {Dagstuhl, Germany}, URL = {http://drops.dagstuhl.de/opus/volltexte/2005/354}, annote = {Keywords: Temporal information extraction, annotation, temporal reasoning, events} }
    01/2005;

Publication Stats

413 Citations
0.66 Total Impact Points

Institutions

  • 2008–2010
    • Thomson Reuters
      New York City, New York, United States
  • 2007–2009
    • Brandeis University
      • Department of Computer Science
      Waltham, MA, United States
    • St. Joseph's Hospital, St. Paul, Minnesota
      Minneapolis, Minnesota, United States
  • 1998–2004
    • Universität Hamburg
      • Department of Informatics
      Hamburg, Hamburg, Germany