| 词汇 | example_english_information-retrieval |
| 释义 | Examples of information retrievalThese examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. Ontologies have come into widespread use in many fields, including knowledge representation and integration, informationretrieval and extraction, and conceptual model design. After the preprocessing has been done, we parse the text, using the same type of parser as in informationretrieval. Applications are found in composition, informationretrieval and music theory. Capturing multimodal design activities in support of informationretrieval and process analysis. In informationretrieval, for instance, stored descriptions must often be compared with one another, and the basic operation below is once again unification. It is related to number theory, algebra and category theory, and it has applications to information retrieval systems, automatic code generation, data transformations and coding. Informationretrieval and information-filtering systems are applicable in order to minimize search difficulties, aiming to aid the user in the search for worthwhile information. However, recall and precision measures derived from informationretrieval have to be adjusted for the task of word alignment. The conceptualization of "reading" as an active process of sign-making, and not just information retrieval, supports both creative and oppositional meaning making. This will be achieved through the effective processing of visual typological knowledge leading to design informationretrieval and interpretation by the framework software modules. The difficulty of pinpointing and verifying the precise answer makes question answering more challenging than the common informationretrieval task done by search engines. One of the reasons that textual informationretrieval is so well suited to pure functional programming is that the database is essentially static. The informationretrieval engine selects a subset of the available documents based on a number of keywords derived from the question at hand. Finally, it can be directly and/or indirectly employed for other informationretrieval problems. Since we want to compare word frequencies in different sentences, we must consider each sentence as a separate document (in the terminology of informationretrieval). Informationretrieval by means of the computer's search engine takes much less time than thumbing through the pages of an alphabetic dictionary. His research interests include engineering informationretrieval, ontology engineering, design theory and methodology, and computeraided design. Examples of such artifacts include speech recognizers, machine translation systems, natural-language interfaces to databases or software systems, and informationretrieval systems. Informationretrieval and author identification are two such cases. Consequently, this methodology is promising, and the segmentation system would be helpful for application systems such as machine translation and informationretrieval. Nominal parsing is the pre-step for nominal interpretation and also a crucial step in applications such as informationretrieval. It is also stimulating cross-fertilisation of ideas between researchers in natural language processing, informationretrieval and artificial intelligence. Personalised informationretrieval from public and corporate information sources. Traditionally, this has been of particular relevance for user modelling in the areas of informationretrieval and personalized news recommender systems. These include hybrid reasoning, task decomposition, informationretrieval, document generation and knowledge acquisition. It applies techniques of informationretrieval and machine learning. So for systems in which there is no semantic analysis or no reasoning (such as informationretrieval systems), statistical methods are applicable. In informationretrieval there is currently a considerable interest in probabilistically modeling textual contents. A table of contents is also convenient in systems that assist in informationretrieval and selection. An example is the word clusters formed through document comparisons during informationretrieval. This system also integrated informationretrieval techniques to give users access to legal treatises. Informationretrieval is, in most cases, concerned with the process of matching a user's statement of their information needs with a collection of documents. These include improving design informationretrieval to achieve a more coherent environment for design exploration, learning, and reuse. One critical issue here is the construction of a structured representation for indexing documents to improve informationretrieval. Biomimetic design through natural language analysis to facilitate cross-domain informationretrieval. An ontology-based retrieval algorithm is developed to support the design informationretrieval. Logic-based models were launched to provide a rich and uniform representation of information and its semantics with the aim to improve informationretrieval eectiveness. In turn, the frame-systems are interconnected in an informationretrieval network. The exclusion of 'untopical' open-class words, such as know, find, and world, is well-precedented in informationretrieval. Ideally, the tables of contents should be evaluated extrinsically in different tasks, among which the most important being informationretrieval and text summarization. In the informationretrieval case, though, we may not be told which documents are relevant and which are not. A number of systems in this evaluation have successfully combined informationretrieval and natural language processing techniques. In the case of query processing, an initial stage of simple matching is carried out, using standard keyword-based informationretrieval weighting schemes. However, we consider both portals and informationretrieval as supporting technology and not applications on their own. Section 3 presents methodologies for the evaluation of the information selection process, which are borrowed from the evaluation of informationretrieval and information filtering systems. Extensions to the notion of isomorphism will permit a study of the development of informationretrieval applications in a much larger context. In informationretrieval, it is common to identify phrasal terms from queries and generate their variants for query expansion. He has authored many papers on process migration, fault tolerant routing protocols and informationretrieval topics. To do this, the workbench uses methods from computational linguistics, informationretrieval and knowledge engineering. Interactive informationretrieval based on faceted classification using views. Adapting a full-text informationretrieval system to the computer troubleshooting domain. In the evaluation of different methods and models for informationretrieval usually a number of queries are used. Should we translate the documents or the queries in cross-language informationretrieval? This research contributes to the development and use of engineering ontology for design informationretrieval. To improve the performance of design informationretrieval, we have developed ontology-based query processing, where users' requests are interpreted based on their domain-specific meanings. These keywords were used as informationretrieval queries into a range of databases. The framework enables the development of knowledge-based systems that integrate a variety of inference procedures, combine informationretrieval with reasoning and facilitate automated document drafting. In this paper we focus on the combination of contextualization and personalization methods to improve the performance of personalized informationretrieval. Text fields are usually represented as sets of linguistic items (for example, words reduced by some stemming algorithm) similar to vector representations in informationretrieval. Characteristic examples of relevant application domains include manufacturing control, network management, informationretrieval and traffic management. Accordingly, among the application areas for the new modelling paradigm are informationretrieval and speech recognition. The section on applications and techniques covers diverse areas like clustering, text alignment, machine translation, informationretrieval and text categorization. In most informationretrieval systems, the terms are words, possibly stemmed, and with stop words removed. More generally, it is useful for most applications in informationretrieval and information extraction. In informationretrieval terms, mediation may increase recall at the expense of precision. The approximation is obtained using similarity metrics for text from informationretrieval. During the last forty years, a plethora of informationretrieval models and their variations have emerged. These systems look like ordinary informationretrieval systems on the surface, but allow the user to specify their information needs more accurately by 'translating' query terms into semantic entities. In the area of informationretrieval and management, they included developing semi-automatic approaches that allow users, devices, and applications to extract from their environment the necessary information to operate. That said, the book is still however to be recommended to advanced undergraduate, masters and early stage doctoral students in informationretrieval, machine translation, translation studies and related topics. The principal contribution of this work is to characterise the document space resulting from informationretrieval techniques and to demonstrate the approach for mixture language modelling. All three model parameters directly relate to quantities of immediate interest to speech recognition, reflecting an intimate relation between modelling of word occurrence for speech recognition and informationretrieval. For design informationretrieval, we propose to use shallow natural language processing and domain-specific design ontology to automatically construct a structured and semantics-based representation from unstructured design documents. But the world of informationretrieval now moves faster than many printed sources allow; there are as yet few guidelines for the use of, for example, on-line sources or websites. The answer is that it has been kept within learnable bounds by the limitations of human information retrieval, memory, perception, and learning - including second-language\\second-dialect learning. We also perceive the importance of design informationretrieval from three further aspects, where queries should be treated in a broader and more abstract manner: design exploration, learning, and reuse. Subjective and objective categories are potentially important for text processing applications, such as information extraction and informationretrieval, where the evidential status of information is important. In addition to stemming errors, stems produced by suffix removal are often not words, which makes it difficult to use them for any purpose other than informationretrieval. A number of stories are about reasonably established companies in the document processing space whose bread and butter still seems to be term-based informationretrieval and document categorisation. Compare: retrieval of information - informationretrieval participation by students - student participation. The informationretrieval query takes all variable names and values in addition to a list of terms associated with each generic argument in order to generate a query. In the informationretrieval application, the training set consists of a query (a set of one or more relevant documents and a set of zero or more irrelevant documents). A related term is informationretrieval. We describe a framework designed to automatically construct a structured representation model from an unstructured design document to achieve a more effective way of design informationretrieval. An example of the latter is for the user to ask for documents containing the phrase "information retrieval" and any documents containing the word "information" and the word "retrieval". Both content analysis and informationretrieval can benefit from semantic disambiguation because they are ideally based on concepts, not the often conceptually ambiguous words used to specify concepts. For certain applications, typically one-domain informationretrieval tasks, a combination of implicit and explicit prompts which make system limitations clear for the user are likely to be successful. They have addressed different tasks, for instance speech recognition and informationretrieval, within a common evaluation framework focused on technology assessment using a carefully controlled train-test-measure protocol. These researchers are engaged in activities ranging from natural language dialog, information retrieval, topic-tracking, named-entity detection, document classification and machine translation to bioinformatics and open-domain question answering. Auto-encoding of documents for informationretrieval systems. Matrices, vector spaces, and informationretrieval. Ethics, genomics, and informationretrieval. These examples are from corpora and from sources on the web. Any opinions in the examples do not represent the opinion of the Cambridge Dictionary editors or of Cambridge University Press or its licensors. |
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