Vocabulary 4
Automatic summarization is the process of reducing a text document with a computer program in order to create a summary that retains the most important points of the original document.
Anaphora resolution is the problem of resolving what a pronoun, or a noun phrase refers to.
Discourse analysis is a general term for a number of approaches to analyzing written, vocal, or sign language use or any significant semiotic event.
Speech act is the performance of an utterance:
Al-complete or AI-hard, implies that the difficulty of the computational problems is equivalent to solving the central artificial intelligence problem- making computers as intelligent as people
Morphological segmentation is separation of words into individual morphemes and identifying the class of the morphemes.
Named entity recognition (NER) is a subtask of information extraction that seeks to locate and classify atomic elements in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
Capitalization is writing a word with its first letter as a capital letter (upper-case letter) and the remaining letters in lower case.
Natural language generation is the natural language processing task of generating natural language from a machine representation system such as a knowledge base or a logical form.
Natural language understanding is a subtopic of natural language processing in artificial intelligence that deals with machine reading comprehension.
First-order logic is symbolized reasoning in which each sentence, or statement, is broken down into a subject and a predicate. The predicate modifies or defines the properties of the subject. In first-order logic, a predicate can only refer to a single subject.
Metamodel is a simplified or approximated descriptive model of another descriptive model.
Closed world assumption is the presumption that what is not currently known to be true is false.
Open world assumption states that lack of knowledge does not imply falsity
Optical character recognition is the mechanical or electronic conversion of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used as a form of data entry from some sort of original paper data source, whether documents, sales receipts, mail, or any number of printed records. It is a common method of digitizing printed texts so that they can be electronically searched, stored more compactly, displayed on-line, and used in machine processes.
Part-of-speech tagging also called grammatical tagging or word-category disambiguation, is the process of marking up a word in a text (corpus) as corresponding to a particular part of speech, based on both its definition, as well as its context—i.e. relationship with adjacent and related words in a phrase, sentence, or paragraph. In the context of computational linguistics, it uses algorithms which associate discrete terms, as well as hidden parts of speech, in accordance with a set of descriptive tags.
Parsing is the process of analyzing a string of symbols, either in natural language or in computer languages, according to the rules of a formal grammar.
Parse tree is an ordered, rooted tree that represents the syntactic structure of a string according to some formal grammar.
Sentiment analyses aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. The attitude may be his or her judgment or evaluation (see appraisal theory), affective state (that is to say, the emotional state of the author when writing), or the intended emotional communication (that is to say, the emotional effect the author wishes to have on the reader).
Word-sense disambiguation is an open problem of natural language processing, which governs the process of identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings.
Information retrieval (IR) is the activity of obtaining information resources relevant to an information need from a collection of information resources.
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine- readable documents. In most of the cases this activity concerns processing human language texts by means of natural language processing
Stemming is the process of reducing inflected (or sometimes derived) words to their stem, base or root form—generally a written word form. The stem need not be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root.
Text simplification is an operation used in natural language processing to modify, enhance, classify or otherwise process an existing corpus of human-readable text in such a way that the grammar and structure of the prose is greatly simplified, while the underlying meaning and information remains the same.
Text-proofing is reading (copying or proofing) in order to find errors and mark corrections.
Natural language search is a search using regular spoken language, such as English. Using this type of search you can ask the database a question or you can type in a sentence that describes the information you are looking for. The database then uses a programmed logic to determine the keywords in the sentence by their position in the sentence.
Query expansion is the process of reformulating a seed query to improve retrieval performance in information retrieval operations. In the context of web search engines, query expansion involves evaluating a user's input (what words were typed into the search query area, and sometimes other types of data) and expanding the search query to match additional documents.
Automated essay scoring is the use of specialized computer programs to assign grades to essays written in an educational setting. It is a method of educational assessment and an application of natural language processing. Its objective is to classify a large set of textual entities into a small number of discrete categories, corresponding to the possible grades.
Automated planning and scheduling is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles.
Trial and error is the process of experimenting with various methods of doing something until one finds the most successful.
Dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems.
Reinforcement learning is an area of machine learning in computer science, concerned with how an agent ought to take actions in an environment so as to maximize some notion of cumulative reward.
Combinatorial optimization is a topic that consists of finding an optimal object from a finite set of objects.
Action language is a language for specifying state transition systems, and is commonly used to create formal models of the effects of actions on the world. Action languages are commonly used in the artificial intelligence and robotics domains, where they describe how actions affect the states of systems over time, and may be used for automated planning.
Markov decision processes provide a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for studying a wide range of optimization problems solved via dynamic programming and reinforcement learning.
Partially observable Markov decision process (POMDP) models an agent decision process in which it is assumed that the system dynamics are determined by an MDP, but the agent cannot directly observe the underlying state. Instead, it must maintain a probability distribution over the set of possible states, based on a set of observations and observation probabilities, and the underlying MDP.
Multi-agent planning involves coordinating the resources and activities of multiple "agents".
STRIPS (Stanford Research Institute Problem Solver) is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. A STRIPS instance is composed of: An initial state; The specification of the goal states - situations which the planner is trying to reach; A set of actions. For each action, the following are included: preconditions (what must be established before the action is performed); postconditions (what is established after the action is performed).,
PDDL (Planning Domain Definition Language) IS standard encoding language for “classical” planning tasks. Components of a PDDL planning task: Objects: Things in the world that interest us; Predicates: Properties of objects that we are interested in; can be true or false; Initial state; The state of the world that we start in; Goal specification: Things that we want to be true; Actions/Operators: Ways of changing the state of the world.
Hierarchical task network is an approach to automated planning in which the dependency among actions can be given in the form of networks.
Machine vision refers to a process of combining automated image analysis with other methods and technologies to provide automated inspection and robot guidance in industrial applications.
Automated theorem proving (ATP or automated deduction) is a subfield of automated reasoning dealing with proving mathematical theorems by computer programs.
Speech recognition (SR) is the translation of spoken words into text.
Domotics is a field which involves the creation of automated controls for homes, ranging from lights which click on when someone enters a room to smart washing machines which select the appropriate cycle and time for a load of clothing. People may refer to domotics as home automation or "smart home systems," depending on the region they live in and their approach to the field. Domotics can encompass both hardware and software, with customized systems built specifically for the purpose along with existing systems which are modified.
Speech-to-text processing is the process of converting speech into its textual equivalent. It allows applying text processing solutions to audio inputs coming from different sources (phone conversations, voice messages, radio ...)
Voice recognition refers to finding the identity of "who" is speaking, rather than what they are saying.
General game playing is the design of artificial intelligence programs to be able to play more than one game successfully.
Hands free computing is any Computer configuration where a user can interface without the use of their hands, an otherwise common requirement of human interface devices such as the mouse and keyboard.
Multimodal interaction is providing the user with multiple modes of interfacing with a system.
Telematics is any integrated use of telecommunications and informatics
De-duplication refers generally to eliminating duplicate or redundant information.
The inference engine is a computer program designed to produce a reasoning on rules.
Forward chaining is the questioning of an expert who has no idea of the solution and investigates progressively.
Backward chaining is when the engine has an idea of the target
Mixed chaining the engine has an idea of the goal but it is not enough: it deduces in forward chaining from previous user responses all that is possible before asking the next question.