-
Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004)
0.22
0.21678177 = product of:
0.2709772 = sum of:
0.03980924 = product of:
0.19904618 = sum of:
0.19904618 = weight(_text_:3a in 562) [ClassicSimilarity], result of:
0.19904618 = score(doc=562,freq=2.0), product of:
0.35416332 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.04177434 = queryNorm
0.56201804 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.2 = coord(1/5)
0.19904618 = weight(_text_:2f in 562) [ClassicSimilarity], result of:
0.19904618 = score(doc=562,freq=2.0), product of:
0.35416332 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.04177434 = queryNorm
0.56201804 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.015142222 = weight(_text_:of in 562) [ClassicSimilarity], result of:
0.015142222 = score(doc=562,freq=10.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.23179851 = fieldWeight in 562, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.016979538 = product of:
0.033959076 = sum of:
0.033959076 = weight(_text_:22 in 562) [ClassicSimilarity], result of:
0.033959076 = score(doc=562,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.23214069 = fieldWeight in 562, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=562)
0.5 = coord(1/2)
0.8 = coord(4/5)
- Abstract
- Document representations for text classification are typically based on the classical Bag-Of-Words paradigm. This approach comes with deficiencies that motivate the integration of features on a higher semantic level than single words. In this paper we propose an enhancement of the classical document representation through concepts extracted from background knowledge. Boosting is used for actual classification. Experimental evaluations on two well known text corpora support our approach through consistent improvement of the results.
- Content
- Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
- Date
- 8. 1.2013 10:22:32
- Source
- Proceedings of the 4th IEEE International Conference on Data Mining (ICDM 2004), 1-4 November 2004, Brighton, UK
-
Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
0.15
0.1523986 = product of:
0.25399765 = sum of:
0.03980924 = product of:
0.19904618 = sum of:
0.19904618 = weight(_text_:3a in 862) [ClassicSimilarity], result of:
0.19904618 = score(doc=862,freq=2.0), product of:
0.35416332 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.04177434 = queryNorm
0.56201804 = fieldWeight in 862, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=862)
0.2 = coord(1/5)
0.19904618 = weight(_text_:2f in 862) [ClassicSimilarity], result of:
0.19904618 = score(doc=862,freq=2.0), product of:
0.35416332 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.04177434 = queryNorm
0.56201804 = fieldWeight in 862, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=862)
0.015142222 = weight(_text_:of in 862) [ClassicSimilarity], result of:
0.015142222 = score(doc=862,freq=10.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.23179851 = fieldWeight in 862, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=862)
0.6 = coord(3/5)
- Abstract
- This research revisits the classic Turing test and compares recent large language models such as ChatGPT for their abilities to reproduce human-level comprehension and compelling text generation. Two task challenges- summary and question answering- prompt ChatGPT to produce original content (98-99%) from a single text entry and sequential questions initially posed by Turing in 1950. We score the original and generated content against the OpenAI GPT-2 Output Detector from 2019, and establish multiple cases where the generated content proves original and undetectable (98%). The question of a machine fooling a human judge recedes in this work relative to the question of "how would one prove it?" The original contribution of the work presents a metric and simple grammatical set for understanding the writing mechanics of chatbots in evaluating their readability and statistical clarity, engagement, delivery, overall quality, and plagiarism risks. While Turing's original prose scores at least 14% below the machine-generated output, whether an algorithm displays hints of Turing's true initial thoughts (the "Lovelace 2.0" test) remains unanswerable.
- Source
- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
-
Blair, D.C.: Information retrieval and the philosophy of language (2002)
0.04
0.039681207 = product of:
0.09920301 = sum of:
0.0795246 = weight(_text_:philosophy in 4283) [ClassicSimilarity], result of:
0.0795246 = score(doc=4283,freq=4.0), product of:
0.23055021 = queryWeight, product of:
5.5189433 = idf(docFreq=481, maxDocs=44218)
0.04177434 = queryNorm
0.34493396 = fieldWeight in 4283, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
5.5189433 = idf(docFreq=481, maxDocs=44218)
0.03125 = fieldNorm(doc=4283)
0.019678416 = weight(_text_:of in 4283) [ClassicSimilarity], result of:
0.019678416 = score(doc=4283,freq=38.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.30123898 = fieldWeight in 4283, product of:
6.164414 = tf(freq=38.0), with freq of:
38.0 = termFreq=38.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.03125 = fieldNorm(doc=4283)
0.4 = coord(2/5)
- Abstract
- Information retrieval - the retrieval, primarily, of documents or textual material - is fundamentally a linguistic process. At the very least we must describe what we want and match that description with descriptions of the information that is available to us. Furthermore, when we describe what we want, we must mean something by that description. This is a deceptively simple act, but such linguistic events have been the grist for philosophical analysis since Aristotle. Although there are complexities involved in referring to authors, document types, or other categories of information retrieval context, here I wish to focus an one of the most problematic activities in information retrieval: the description of the intellectual content of information items. And even though I take information retrieval to involve the description and retrieval of written text, what I say here is applicable to any information item whose intellectual content can be described for retrieval-books, documents, images, audio clips, video clips, scientific specimens, engineering schematics, and so forth. For convenience, though, I will refer only to the description and retrieval of documents. The description of intellectual content can go wrong in many obvious ways. We may describe what we want incorrectly; we may describe it correctly but in such general terms that its description is useless for retrieval; or we may describe what we want correctly, but misinterpret the descriptions of available information, and thereby match our description of what we want incorrectly. From a linguistic point of view, we can be misunderstood in the process of retrieval in many ways. Because the philosophy of language deals specifically with how we are understood and mis-understood, it should have some use for understanding the process of description in information retrieval. First, however, let us examine more closely the kinds of misunderstandings that can occur in information retrieval. We use language in searching for information in two principal ways. We use it to describe what we want and to discriminate what we want from other information that is available to us but that we do not want. Description and discrimination together articulate the goals of the information search process; they also delineate the two principal ways in which language can fail us in this process. Van Rijsbergen (1979) was the first to make this distinction, calling them "representation" and "discrimination.""
- Source
- Annual review of information science and technology. 37(2003), S.3-50
-
Bedathur, S.; Narang, A.: Mind your language : effects of spoken query formulation on retrieval effectiveness (2013)
0.03
0.03223907 = product of:
0.08059767 = sum of:
0.017665926 = weight(_text_:of in 1150) [ClassicSimilarity], result of:
0.017665926 = score(doc=1150,freq=10.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.2704316 = fieldWeight in 1150, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0546875 = fieldNorm(doc=1150)
0.062931746 = product of:
0.12586349 = sum of:
0.12586349 = weight(_text_:mind in 1150) [ClassicSimilarity], result of:
0.12586349 = score(doc=1150,freq=2.0), product of:
0.2607373 = queryWeight, product of:
6.241566 = idf(docFreq=233, maxDocs=44218)
0.04177434 = queryNorm
0.48272148 = fieldWeight in 1150, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
6.241566 = idf(docFreq=233, maxDocs=44218)
0.0546875 = fieldNorm(doc=1150)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- Voice search is becoming a popular mode for interacting with search engines. As a result, research has gone into building better voice transcription engines, interfaces, and search engines that better handle inherent verbosity of queries. However, when one considers its use by non- native speakers of English, another aspect that becomes important is the formulation of the query by users. In this paper, we present the results of a preliminary study that we conducted with non-native English speakers who formulate queries for given retrieval tasks. Our results show that the current search engines are sensitive in their rankings to the query formulation, and thus highlights the need for developing more robust ranking methods.
-
Dorr, B.J.: Large-scale dictionary construction for foreign language tutoring and interlingual machine translation (1997)
0.03
0.028363807 = product of:
0.04727301 = sum of:
0.009978054 = product of:
0.04989027 = sum of:
0.04989027 = weight(_text_:problem in 3244) [ClassicSimilarity], result of:
0.04989027 = score(doc=3244,freq=2.0), product of:
0.17731056 = queryWeight, product of:
4.244485 = idf(docFreq=1723, maxDocs=44218)
0.04177434 = queryNorm
0.28137225 = fieldWeight in 3244, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.244485 = idf(docFreq=1723, maxDocs=44218)
0.046875 = fieldNorm(doc=3244)
0.2 = coord(1/5)
0.02031542 = weight(_text_:of in 3244) [ClassicSimilarity], result of:
0.02031542 = score(doc=3244,freq=18.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.3109903 = fieldWeight in 3244, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=3244)
0.016979538 = product of:
0.033959076 = sum of:
0.033959076 = weight(_text_:22 in 3244) [ClassicSimilarity], result of:
0.033959076 = score(doc=3244,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.23214069 = fieldWeight in 3244, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=3244)
0.5 = coord(1/2)
0.6 = coord(3/5)
- Abstract
- Describes techniques for automatic construction of dictionaries for use in large-scale foreign language tutoring (FLT) and interlingual machine translation (MT) systems. The dictionaries are based on a language independent representation called lexical conceptual structure (LCS). Demonstrates that synonymous verb senses share distribution patterns. Shows how the syntax-semantics relation can be used to develop a lexical acquisition approach that contributes both toward the enrichment of existing online resources and toward the development of lexicons containing more complete information than is provided in any of these resources alone. Describes the structure of the LCS and shows how this representation is used in FLT and MT. Focuses on the problem of building LCS dictionaries for large-scale FLT and MT. Describes authoring tools for manual and semi-automatic construction of LCS dictionaries. Presents an approach that uses linguistic techniques for building word definitions automatically. The techniques have been implemented as part of a set of lixicon-development tools used in the MILT FLT project
- Date
- 31. 7.1996 9:22:19
-
Warner, J.: Analogies between linguistics and information theory (2007)
0.03
0.027557282 = product of:
0.0688932 = sum of:
0.023941955 = weight(_text_:of in 138) [ClassicSimilarity], result of:
0.023941955 = score(doc=138,freq=36.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.36650562 = fieldWeight in 138, product of:
6.0 = tf(freq=36.0), with freq of:
36.0 = termFreq=36.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=138)
0.04495125 = product of:
0.0899025 = sum of:
0.0899025 = weight(_text_:mind in 138) [ClassicSimilarity], result of:
0.0899025 = score(doc=138,freq=2.0), product of:
0.2607373 = queryWeight, product of:
6.241566 = idf(docFreq=233, maxDocs=44218)
0.04177434 = queryNorm
0.34480107 = fieldWeight in 138, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
6.241566 = idf(docFreq=233, maxDocs=44218)
0.0390625 = fieldNorm(doc=138)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- An analogy is established between the syntagm and paradigm from Saussurean linguistics and the message and messages for selection from the information theory initiated by Claude Shannon. The analogy is pursued both as an end in itself and for its analytic value in understanding patterns of retrieval from full-text systems. The multivalency of individual words when isolated from their syntagm is contrasted with the relative stability of meaning of multiword sequences, when searching ordinary written discourse. The syntagm is understood as the linear sequence of oral and written language. Saussure's understanding of the word, as a unit that compels recognition by the mind, is endorsed, although not regarded as final. The lesser multivalency of multiword sequences is understood as the greater determination of signification by the extended syntagm. The paradigm is primarily understood as the network of associations a word acquires when considered apart from the syntagm. The restriction of information theory to expression or signals, and its focus on the combinatorial aspects of the message, is sustained. The message in the model of communication in information theory can include sequences of written language. Shannon's understanding of the written word, as a cohesive group of letters, with strong internal statistical influences, is added to the Saussurean conception. Sequences of more than one word are regarded as weakly correlated concatenations of cohesive units.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.3, S.309-321
-
Ponte, J.M.: Language models for relevance feedback (2000)
0.03
0.026994044 = product of:
0.06748511 = sum of:
0.013543615 = weight(_text_:of in 35) [ClassicSimilarity], result of:
0.013543615 = score(doc=35,freq=8.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.20732689 = fieldWeight in 35, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=35)
0.053941496 = product of:
0.10788299 = sum of:
0.10788299 = weight(_text_:mind in 35) [ClassicSimilarity], result of:
0.10788299 = score(doc=35,freq=2.0), product of:
0.2607373 = queryWeight, product of:
6.241566 = idf(docFreq=233, maxDocs=44218)
0.04177434 = queryNorm
0.41376126 = fieldWeight in 35, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
6.241566 = idf(docFreq=233, maxDocs=44218)
0.046875 = fieldNorm(doc=35)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- The language modeling approach to Information Retrieval (IR) is a conceptually simple model of IR originally developed by Ponte and Croft (1998). In this approach, the query is treated as a random event and documents are ranked according to the likelihood that the query would be generated via a language model estimated for each document. The intuition behind this approach is that users have a prototypical document in mind and will choose query terms accordingly. The intuitive appeal of this method is that inferences about the semantic content of documents do not need to be made resulting in a conceptually simple model. In this paper, techniques for relevance feedback and routing are derived from the language modeling approach in a straightforward manner and their effectiveness is demonstrated empirically. These experiments demonstrate further proof of concept for the language modeling approach to retrieval
-
Warner, A.J.: Natural language processing (1987)
0.03
0.02533477 = product of:
0.06333692 = sum of:
0.018058153 = weight(_text_:of in 337) [ClassicSimilarity], result of:
0.018058153 = score(doc=337,freq=2.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.27643585 = fieldWeight in 337, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.125 = fieldNorm(doc=337)
0.045278773 = product of:
0.090557545 = sum of:
0.090557545 = weight(_text_:22 in 337) [ClassicSimilarity], result of:
0.090557545 = score(doc=337,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.61904186 = fieldWeight in 337, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.125 = fieldNorm(doc=337)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Source
- Annual review of information science and technology. 22(1987), S.79-108
-
Bian, G.-W.; Chen, H.-H.: Cross-language information access to multilingual collections on the Internet (2000)
0.02
0.023212025 = product of:
0.038686708 = sum of:
0.009978054 = product of:
0.04989027 = sum of:
0.04989027 = weight(_text_:problem in 4436) [ClassicSimilarity], result of:
0.04989027 = score(doc=4436,freq=2.0), product of:
0.17731056 = queryWeight, product of:
4.244485 = idf(docFreq=1723, maxDocs=44218)
0.04177434 = queryNorm
0.28137225 = fieldWeight in 4436, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.244485 = idf(docFreq=1723, maxDocs=44218)
0.046875 = fieldNorm(doc=4436)
0.2 = coord(1/5)
0.011729115 = weight(_text_:of in 4436) [ClassicSimilarity], result of:
0.011729115 = score(doc=4436,freq=6.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.17955035 = fieldWeight in 4436, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=4436)
0.016979538 = product of:
0.033959076 = sum of:
0.033959076 = weight(_text_:22 in 4436) [ClassicSimilarity], result of:
0.033959076 = score(doc=4436,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.23214069 = fieldWeight in 4436, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=4436)
0.5 = coord(1/2)
0.6 = coord(3/5)
- Abstract
- Language barrier is the major problem that people face in searching for, retrieving, and understanding multilingual collections on the Internet. This paper deals with query translation and document translation in a Chinese-English information retrieval system called MTIR. Bilingual dictionary and monolingual corpus-based approaches are adopted to select suitable tranlated query terms. A machine transliteration algorithm is introduced to resolve proper name searching. We consider several design issues for document translation, including which material is translated, what roles the HTML tags play in translation, what the tradeoff is between the speed performance and the translation performance, and what from the translated result is presented in. About 100.000 Web pages translated in the last 4 months of 1997 are used for quantitative study of online and real-time Web page translation
- Date
- 16. 2.2000 14:22:39
- Source
- Journal of the American Society for Information Science. 51(2000) no.3, S.281-296
-
Ruge, G.: ¬A spreading activation network for automatic generation of thesaurus relationships (1991)
0.02
0.022167925 = product of:
0.05541981 = sum of:
0.015800884 = weight(_text_:of in 4506) [ClassicSimilarity], result of:
0.015800884 = score(doc=4506,freq=2.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.24188137 = fieldWeight in 4506, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.109375 = fieldNorm(doc=4506)
0.039618924 = product of:
0.07923785 = sum of:
0.07923785 = weight(_text_:22 in 4506) [ClassicSimilarity], result of:
0.07923785 = score(doc=4506,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.5416616 = fieldWeight in 4506, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.109375 = fieldNorm(doc=4506)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Date
- 8.10.2000 11:52:22
-
Baayen, R.H.; Lieber, H.: Word frequency distributions and lexical semantics (1997)
0.02
0.022167925 = product of:
0.05541981 = sum of:
0.015800884 = weight(_text_:of in 3117) [ClassicSimilarity], result of:
0.015800884 = score(doc=3117,freq=2.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.24188137 = fieldWeight in 3117, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.109375 = fieldNorm(doc=3117)
0.039618924 = product of:
0.07923785 = sum of:
0.07923785 = weight(_text_:22 in 3117) [ClassicSimilarity], result of:
0.07923785 = score(doc=3117,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.5416616 = fieldWeight in 3117, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.109375 = fieldNorm(doc=3117)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- Relation between meaning, lexical productivity and frequency of use
- Date
- 28. 2.1999 10:48:22
-
Byrne, C.C.; McCracken, S.A.: ¬An adaptive thesaurus employing semantic distance, relational inheritance and nominal compound interpretation for linguistic support of information retrieval (1999)
0.02
0.021245057 = product of:
0.05311264 = sum of:
0.019153563 = weight(_text_:of in 4483) [ClassicSimilarity], result of:
0.019153563 = score(doc=4483,freq=4.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.2932045 = fieldWeight in 4483, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.09375 = fieldNorm(doc=4483)
0.033959076 = product of:
0.06791815 = sum of:
0.06791815 = weight(_text_:22 in 4483) [ClassicSimilarity], result of:
0.06791815 = score(doc=4483,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.46428138 = fieldWeight in 4483, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.09375 = fieldNorm(doc=4483)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Date
- 15. 3.2000 10:22:37
- Source
- Journal of information science. 25(1999) no.2, S.113-131
-
Hutchins, J.: From first conception to first demonstration : the nascent years of machine translation, 1947-1954. A chronology (1997)
0.02
0.02034877 = product of:
0.050871924 = sum of:
0.022572692 = weight(_text_:of in 1463) [ClassicSimilarity], result of:
0.022572692 = score(doc=1463,freq=8.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.34554482 = fieldWeight in 1463, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.078125 = fieldNorm(doc=1463)
0.028299233 = product of:
0.056598466 = sum of:
0.056598466 = weight(_text_:22 in 1463) [ClassicSimilarity], result of:
0.056598466 = score(doc=1463,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.38690117 = fieldWeight in 1463, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.078125 = fieldNorm(doc=1463)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- Chronicles the early history of applying electronic computers to the task of translating natural languages, from the 1st suggestions by Warren Weaver in Mar 1947 to the 1st demonstration of a working, if limited, program in Jan 1954
- Date
- 31. 7.1996 9:22:19
-
Yang, C.C.; Luk, J.: Automatic generation of English/Chinese thesaurus based on a parallel corpus in laws (2003)
0.02
0.019490778 = product of:
0.03248463 = sum of:
0.005820531 = product of:
0.029102655 = sum of:
0.029102655 = weight(_text_:problem in 1616) [ClassicSimilarity], result of:
0.029102655 = score(doc=1616,freq=2.0), product of:
0.17731056 = queryWeight, product of:
4.244485 = idf(docFreq=1723, maxDocs=44218)
0.04177434 = queryNorm
0.1641338 = fieldWeight in 1616, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.244485 = idf(docFreq=1723, maxDocs=44218)
0.02734375 = fieldNorm(doc=1616)
0.2 = coord(1/5)
0.016759368 = weight(_text_:of in 1616) [ClassicSimilarity], result of:
0.016759368 = score(doc=1616,freq=36.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.25655392 = fieldWeight in 1616, product of:
6.0 = tf(freq=36.0), with freq of:
36.0 = termFreq=36.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.02734375 = fieldNorm(doc=1616)
0.009904731 = product of:
0.019809462 = sum of:
0.019809462 = weight(_text_:22 in 1616) [ClassicSimilarity], result of:
0.019809462 = score(doc=1616,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.1354154 = fieldWeight in 1616, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.02734375 = fieldNorm(doc=1616)
0.5 = coord(1/2)
0.6 = coord(3/5)
- Abstract
- The information available in languages other than English in the World Wide Web is increasing significantly. According to a report from Computer Economics in 1999, 54% of Internet users are English speakers ("English Will Dominate Web for Only Three More Years," Computer Economics, July 9, 1999, http://www.computereconomics. com/new4/pr/pr990610.html). However, it is predicted that there will be only 60% increase in Internet users among English speakers verses a 150% growth among nonEnglish speakers for the next five years. By 2005, 57% of Internet users will be non-English speakers. A report by CNN.com in 2000 showed that the number of Internet users in China had been increased from 8.9 million to 16.9 million from January to June in 2000 ("Report: China Internet users double to 17 million," CNN.com, July, 2000, http://cnn.org/2000/TECH/computing/07/27/ china.internet.reut/index.html). According to Nielsen/ NetRatings, there was a dramatic leap from 22.5 millions to 56.6 millions Internet users from 2001 to 2002. China had become the second largest global at-home Internet population in 2002 (US's Internet population was 166 millions) (Robyn Greenspan, "China Pulls Ahead of Japan," Internet.com, April 22, 2002, http://cyberatias.internet.com/big-picture/geographics/article/0,,5911_1013841,00. html). All of the evidences reveal the importance of crosslingual research to satisfy the needs in the near future. Digital library research has been focusing in structural and semantic interoperability in the past. Searching and retrieving objects across variations in protocols, formats and disciplines are widely explored (Schatz, B., & Chen, H. (1999). Digital libraries: technological advances and social impacts. IEEE Computer, Special Issue an Digital Libraries, February, 32(2), 45-50.; Chen, H., Yen, J., & Yang, C.C. (1999). International activities: development of Asian digital libraries. IEEE Computer, Special Issue an Digital Libraries, 32(2), 48-49.). However, research in crossing language boundaries, especially across European languages and Oriental languages, is still in the initial stage. In this proposal, we put our focus an cross-lingual semantic interoperability by developing automatic generation of a cross-lingual thesaurus based an English/Chinese parallel corpus. When the searchers encounter retrieval problems, Professional librarians usually consult the thesaurus to identify other relevant vocabularies. In the problem of searching across language boundaries, a cross-lingual thesaurus, which is generated by co-occurrence analysis and Hopfield network, can be used to generate additional semantically relevant terms that cannot be obtained from dictionary. In particular, the automatically generated cross-lingual thesaurus is able to capture the unknown words that do not exist in a dictionary, such as names of persons, organizations, and events. Due to Hong Kong's unique history background, both English and Chinese are used as official languages in all legal documents. Therefore, English/Chinese cross-lingual information retrieval is critical for applications in courts and the government. In this paper, we develop an automatic thesaurus by the Hopfield network based an a parallel corpus collected from the Web site of the Department of Justice of the Hong Kong Special Administrative Region (HKSAR) Government. Experiments are conducted to measure the precision and recall of the automatic generated English/Chinese thesaurus. The result Shows that such thesaurus is a promising tool to retrieve relevant terms, especially in the language that is not the same as the input term. The direct translation of the input term can also be retrieved in most of the cases.
- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.7, S.671-682
-
Morris, V.: Automated language identification of bibliographic resources (2020)
0.02
0.017902408 = product of:
0.044756018 = sum of:
0.02211663 = weight(_text_:of in 5749) [ClassicSimilarity], result of:
0.02211663 = score(doc=5749,freq=12.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.33856338 = fieldWeight in 5749, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0625 = fieldNorm(doc=5749)
0.022639386 = product of:
0.045278773 = sum of:
0.045278773 = weight(_text_:22 in 5749) [ClassicSimilarity], result of:
0.045278773 = score(doc=5749,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.30952093 = fieldWeight in 5749, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=5749)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- This article describes experiments in the use of machine learning techniques at the British Library to assign language codes to catalog records, in order to provide information about the language of content of the resources described. In the first phase of the project, language codes were assigned to 1.15 million records with 99.7% confidence. The automated language identification tools developed will be used to contribute to future enhancement of over 4 million legacy records.
- Date
- 2. 3.2020 19:04:22
-
Lezius, W.; Rapp, R.; Wettler, M.: ¬A morphology-system and part-of-speech tagger for German (1996)
0.02
0.017704215 = product of:
0.044260535 = sum of:
0.015961302 = weight(_text_:of in 1693) [ClassicSimilarity], result of:
0.015961302 = score(doc=1693,freq=4.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.24433708 = fieldWeight in 1693, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.078125 = fieldNorm(doc=1693)
0.028299233 = product of:
0.056598466 = sum of:
0.056598466 = weight(_text_:22 in 1693) [ClassicSimilarity], result of:
0.056598466 = score(doc=1693,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.38690117 = fieldWeight in 1693, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.078125 = fieldNorm(doc=1693)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Date
- 22. 3.2015 9:37:18
- Source
- Natural language processing and speech technology: Results of the 3rd KONVENS Conference, Bielefeld, October 1996. Ed.: D. Gibbon
-
Basili, R.; Pazienza, M.T.; Velardi, P.: ¬An empirical symbolic approach to natural language processing (1996)
0.02
0.017131606 = product of:
0.042829014 = sum of:
0.02018963 = weight(_text_:of in 6753) [ClassicSimilarity], result of:
0.02018963 = score(doc=6753,freq=10.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.3090647 = fieldWeight in 6753, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0625 = fieldNorm(doc=6753)
0.022639386 = product of:
0.045278773 = sum of:
0.045278773 = weight(_text_:22 in 6753) [ClassicSimilarity], result of:
0.045278773 = score(doc=6753,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.30952093 = fieldWeight in 6753, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=6753)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- Describes and evaluates the results of a large scale lexical learning system, ARISTO-LEX, that uses a combination of probabilisitc and knowledge based methods for the acquisition of selectional restrictions of words in sublanguages. Presents experimental data obtained from different corpora in different doamins and languages, and shows that the acquired lexical data not only have practical applications in natural language processing, but they are useful for a comparative analysis of sublanguages
- Date
- 6. 3.1997 16:22:15
-
Haas, S.W.: Natural language processing : toward large-scale, robust systems (1996)
0.02
0.017131606 = product of:
0.042829014 = sum of:
0.02018963 = weight(_text_:of in 7415) [ClassicSimilarity], result of:
0.02018963 = score(doc=7415,freq=10.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.3090647 = fieldWeight in 7415, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0625 = fieldNorm(doc=7415)
0.022639386 = product of:
0.045278773 = sum of:
0.045278773 = weight(_text_:22 in 7415) [ClassicSimilarity], result of:
0.045278773 = score(doc=7415,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.30952093 = fieldWeight in 7415, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=7415)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- State of the art review of natural language processing updating an earlier review published in ARIST 22(1987). Discusses important developments that have allowed for significant advances in the field of natural language processing: materials and resources; knowledge based systems and statistical approaches; and a strong emphasis on evaluation. Reviews some natural language processing applications and common problems still awaiting solution. Considers closely related applications such as language generation and th egeneration phase of machine translation which face the same problems as natural language processing. Covers natural language methodologies for information retrieval only briefly
- Source
- Annual review of information science and technology. 31(1996), S.83-119
-
Liddy, E.D.: Natural language processing for information retrieval and knowledge discovery (1998)
0.02
0.016862115 = product of:
0.04215529 = sum of:
0.022345824 = weight(_text_:of in 2345) [ClassicSimilarity], result of:
0.022345824 = score(doc=2345,freq=16.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.34207192 = fieldWeight in 2345, product of:
4.0 = tf(freq=16.0), with freq of:
16.0 = termFreq=16.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0546875 = fieldNorm(doc=2345)
0.019809462 = product of:
0.039618924 = sum of:
0.039618924 = weight(_text_:22 in 2345) [ClassicSimilarity], result of:
0.039618924 = score(doc=2345,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.2708308 = fieldWeight in 2345, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=2345)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- Natural language processing (NLP) is a powerful technology for the vital tasks of information retrieval (IR) and knowledge discovery (KD) which, in turn, feed the visualization systems of the present and future and enable knowledge workers to focus more of their time on the vital tasks of analysis and prediction
- Date
- 22. 9.1997 19:16:05
- Imprint
- Urbana-Champaign, IL : Illinois University at Urbana-Champaign, Graduate School of Library and Information Science
- Source
- Visualizing subject access for 21st century information resources: Papers presented at the 1997 Clinic on Library Applications of Data Processing, 2-4 Mar 1997, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign. Ed.: P.A. Cochrane et al
-
Kay, M.: ¬The proper place of men and machines in language translation (1997)
0.02
0.016284827 = product of:
0.040712066 = sum of:
0.020902606 = weight(_text_:of in 1178) [ClassicSimilarity], result of:
0.020902606 = score(doc=1178,freq=14.0), product of:
0.06532493 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.04177434 = queryNorm
0.31997898 = fieldWeight in 1178, product of:
3.7416575 = tf(freq=14.0), with freq of:
14.0 = termFreq=14.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0546875 = fieldNorm(doc=1178)
0.019809462 = product of:
0.039618924 = sum of:
0.039618924 = weight(_text_:22 in 1178) [ClassicSimilarity], result of:
0.039618924 = score(doc=1178,freq=2.0), product of:
0.14628662 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.04177434 = queryNorm
0.2708308 = fieldWeight in 1178, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=1178)
0.5 = coord(1/2)
0.4 = coord(2/5)
- Abstract
- Machine translation stands no chance of filling actual needs for translation because, although there has been progress in relevant areas of computer science, advance in linguistics have not touched the core problems. Cooperative man-machine systems need to be developed, Proposes a translator's amanuensis, incorporating into a word processor some simple facilities peculiar to translation. Gradual enhancements of such a system could lead to the original goal of machine translation
- Content
- Reprint of a Xerox PARC Working Paper which appeared in 1980
- Date
- 31. 7.1996 9:22:19
- Footnote
- Contribution to a special issue devoted to the theme of new tools for human translators
