Statistical approaches to processing natural language text have become dominant in recent years This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear The book contains all the theory and algorithms needed for building NLP tools It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications

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Foundations of Statistical Natural Language Processing

Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

語用論(Pragmatics)を考える

Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking

羟氨苄青霉素引起大疱性类天疱疮样疹

Proceedings of the Fifth Annual Meeting of the Berkeley Linguistics
Society (1979), pp. 325-335

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Semantic mechanisms of humor

The article proposes a general theory of verbal humor, focusing on verbal jokes äs its most representative subset. The theory is an extension and revision ofRaskin's script-based semantic theory of humor and of Attardo's five-level joke representation model. After distinguishing the parameters of the various degrees of similarity among the joke examples, six knowledge resources informing thejoke, namely script oppositions, logicalmechanisms, situationst targets, narrative strategies, and language, are put forward. A hierarchical organization for the six knowledge resources is then discovered on the basis of the asymmetrical binary relations, of the proposed and modified content l tooldichotomy, and, especially, ofthe hypothesized perceptions ofthe relative degrees of similarity. It is also argued that the emerging joke representation model is neutral to the process ofjoke production. The proposed hierarchy enables the concepts of joke variants and invariants, introduced previously by Attardo, to be firmed up, generalized, and äug· mented into a full-fledged taxonomy indexed with regard to the shared knowledge resource values (for example, two jokes may be variants on, that ist sharing, the same script oppositions and logical mechanisms). The resulting general theory of verbal humor is discussed in the light of its relations with various academic disciplines and areas ofresearch äs well äs with the script-based semantic theory of humor, special theories of humor, and incongruity-based theories.

Script theory revis(it)ed: joke similarity and joke representation model

We describe a scheme for watermarking natural language text by embedding small portions of the watermark bit string in the syntactic structure of a number of selected sentences in the text, with both the selection and embedding keyed (via quadratic residue) to a large prime number. Meaning-preserving transformations of sentences of the text (e.g., translation to another natural language) cannot damage the watermark. Meaning-modifying transformations have a probability, of damaging the watermark, proportional to the watermark length over the number of sentences. Having the key is all that is required for reading the watermark. The approach is best suited for longish meaning-rather than style-oriented "expository" texts (e.g., reports, directives, manuals, etc.), of which governments and industry produce in abundance and which need protection more frequently than fiction or poetry, which are not so tolerant of the small meaning-preserving syntactic changes that the scheme implements.

Natural Language Watermarking: Design, Analysis, and a Proof-of-Concept Implementation

Two main results in the area of information hiding in natural language text are presented. A semantically-based scheme dramatically improves the information-hiding capacity of any text through two techniques: (i) modifying the granularity of meaning of individual sentences, whereas our own previous scheme kept the granularity fixed, and (ii) halving the number of sentences affected by the watermark. No longer a long text, short watermark approach, it now makes it possible to watermark short texts, like wire agency reports. Using both the above-mentioned semantic marking scheme and our previous syntactically-based method hides information in a way that reveals any non-trivial tampering with the text (while re-formatting is not considered to be tampering-the problem would be solved trivially otherwise by hiding a hash of the text) with a probability 1-2 -β(n+1) , n being its number of sentences and β a small positive integer based on the extent of co-referencing.

Natural language watermarking and tamperproofing

The paper introduces and advocates an ontological semantic approach to information security. Both the approach and its resources, the ontology and lexicons, are borrowed from the field of natural language processing and adjusted to the needs of the new domain. The approach pursues the ultimate dual goals of inclusion of natural language data sources as an integral part of the overall data sources in information security applications, and formal specification of the information security community know-how for the support of routine and time-efficient measures to prevent and counteract computer attacks. As the first order of the day, the approach is seen by the information security community as a powerful means to organize and unify the terminology and nomenclature of the field.

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Victor Raskin

Papers

Semantic mechanisms of humor

Script theory revis(it)ed: joke similarity and joke representation model

Natural Language Watermarking: Design, Analysis, and a Proof-of-Concept Implementation

Natural language watermarking and tamperproofing

Ontology in information security: a useful theoretical foundation and methodological tool