This paper introduces primitive Optimality Theory (OTP), a linguistically motivated formalization of OT. OTP specifies the class of autosegmental representations, the universal generator Gen, and the two simple families of permissible constraints. In contrast to less restricted theories using Generalized Alignment, OTP's optimal surface forms can be generated with finite-state methods adapted from (Ellison, 1994). Unfortunately these methods take time exponential on the size of the grammar. Indeed the generation problem is shown NP-complete in this sense. ...
The lexicalist approach to Machine Translation offers significant advantages in the development of linguistic descriptions. However, the Shake-and-Bake generation algorithm of (Whitelock, 1992) is NPcomplete. We present a polynomial time algorithm for lexicalist MT generation provided that sufficient information can be transferred to ensure more determinism.
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Use of recombinant lentivirus pseudotyped with vesicular stomatitis virus glycoprotein G for efficient generation of human anti-cancer chimeric T cells by transduction of human peripheral blood lymphocytes in vitro
Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí sinh học đề tài :Use of recombinant lentivirus pseudotyped with vesicular stomatitis virus glycoprotein G for efficient generation of human anti-cancer chimeric T cells by transduction of human peripheral blood lymphocytes in vitro
One problem for the generation of natural language text is determining when to use a sequence of simple sentences and when a single complex one is more appropriate. In this paper, we show how focus of attention is one factor that influences this decision and describe its implementation in a system that generates explanations for a student advisor expert system.
Important factor in political decision-making is a public opinion as well. Therefore, it is very important to raise global ecological awareness and wider public education regarding ecology. Goal of this book is to bring closer to the readers new drive technologies that are intended to environment and nature protection. The book presents modern technique achievements and technologies applied in the implementation of electric vehicles. Special attention was paid to energy efficiency of EV's. Also today's trends, mathematical models and computer design elements of future cars are presented....
This note presents the simplest overlapping generations model. The model is due
to Diamond (1965), who built on earlier work by Samuelson (1958).
Overlapping generations models capture the fact that individuals do not live
forever, but die at some point and thus have finite life-cycles. Overlapping generations
models are especially useful for analysing the macro-economic effects of
different pension systems.
This is the seventh report by the National Research Council Standing Committee
to Review the Research Program of the Partnership for a New Generation
of Vehicles (PNGV). The PNGV program is a cooperative research and development
(R&D) program between the federal government and the United States
Council for Automotive Research (USCAR), whose members are DaimlerChrysler
Corporation, Ford Motor Company, and General Motors Corporation (GM).
Energy efficiency is finally a common sense term. Nowadays almost everyone knows that using energy more efficiently saves money, reduces the emissions of greenhouse gasses and lowers dependence on imported fossil fuels. We are living in a fossil age at the peak of its strength. Competition for securing resources for fuelling economic development is increasing, price of fuels will increase while availability of would gradually decline.
We describe novel aspects of a new natural language generator called Nitrogen. This generator has a highly flexible input representation that allows a spectrum of input from syntactic to semantic depth, and shifts' the burden of many linguistic decisions to the statistical post-processor. The generation algorithm is compositional, making it efficient, yet it also handles non-compositional aspects of language. Nitrogen's design makes it robust and scalable, operating with lexicons and knowledge bases of one hundred thousand entities. ...
Augmented transition network (ATN) grammars have, since their development by Woods [ 7; ~, become the most used method of describing grammars for natural language understanding end question answering systems. The advantages of the ATN notation have been su,naarized as "I) perspicuity, 2) generative power, 3) efficiency of representation, 4) the ability to capture linguistic regularities and generalities, and 5) efficiency of operation., [I ,p.191 ].
In this paper we present a new approach to controlling the behaviour of a natural language generation system by correlating internal decisions taken during free generation of a wide range of texts with the surface stylistic characteristics of the resulting outputs, and using the correlation to control the generator. This contrasts with the generate-andtest architecture adopted by most previous empirically-based generation approaches, offering a more efficient, generic and holistic method of generator control. ...
In this paper we compare two grammar-based generation algorithms: the Semantic-Head-Driven Generation Algorithm (SHDGA), and the Essential Arguments Algorithm (EAA). Both algorithms have successfully addressed several outstanding problems in grammarbased generation, including dealing with non-monotonic compositionality of representation, left-recursion, deadlock-prone rules, and nondeterminism. We concentrate here on the comparison of selected properties: generality, efficiency, and determinism.
An unsupervised part-of-speech (POS) tagging system that relies on graph clustering methods is described. Unlike in current state-of-the-art approaches, the kind and number of different tags is generated by the method itself. We compute and merge two partitionings of word graphs: one based on context similarity of high frequency words, another on log-likelihood statistics for words of lower frequencies. Using the resulting word clusters as a lexicon, a Viterbi POS tagger is trained, which is refined by a morphological component. ...
be used for efficiency by providing a best-first search heuristic to order the parsing agenda. This paper proposes an agenda-based probabilistic chart parsing algorithm which is both robust and efficient. The algorithm, 7)icky 1, is considered robust because it will potentially generate all constituents produced by a pure bottom-up parser and rank these constituents by likelihood. The efficiency of the algorithm is achieved through a technique called probabilistic prediction, which helps the algorithm avoid worst-case behavior. ...
Under categorial grammars that have powerful rules like composition, a simple n-word sentence can have exponentially many parses. Generating all parses is inefficient and obscures whatever true semantic ambiguities are in the input. This paper addresses the problem for a fairly general form of Combinatory Categorial Grammar, by means of an efficient, correct, and easy to implement normal-form parsing technique.
We describe a system of reversible grammar in which, given a logic-grammar specification of a natural language, two efficient PROLOGprograms are derived by an off-line compilation process: a parser and a generator for this language. The centerpiece of the system is the inversion algorithm designed to compute the generator code from the parser's PROLOG code, using the collection of minimal sets of essential arguments (MSEA) for predicates.
We discuss algorithms for generation within the Lambek Theorem Proving Framework. Efficient algorithms for generation in this framework take a semantics-driven strategy. This strategy can be modeled by means of rules in the calculus that are geared to generation, or by means of an algorithm for the Theorem Prover. The latter possibility enables processing of a bidirectional calculus. Therefore Lambek Theorem Proving is a natural candidate for a 'uniform' architecture for natural language parsing and generation.
In the literature, Tree Adjoining Grammars (TAGs) are propagated to be adequate for natural language description - - analysis as well as generation. In this paper we concentrate on the direction of analysis. Especially important for an implementation of that task is how efficiently this can be done, i.e., how readily the word problem can be solved for TAGs. Up to now, a parser with O(n 6) steps in the worst case was known where n is the length of the input string. In this paper, the result is improved to O(n 4 log n) as a new lowest...
Systemic grammar has been used for AI text generation work in the past, but the Implementations have tended be ad hoc or inefficient. This paper presents an approach to systemic text generation where AI problem solving techniques are applied directly to an unadulterated systemic grammar. This approach is made possible by a special relationship between systemic grammar and problem solving: both are organized primarily as choosing from alternatives. The result is simple, efficient text generation firmly based in a linguistic theory. ...