The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Measuring the similarity between strings plays an increasingly important role in many applications such as information retrieval, short answer grading, and conversational agent software. There has been much recent research interest in applying string similarity within Arabic language applications; however, the use of string similarity in Arabic poses a substantial challenge such as the complexity...
Although the volume of online educational resources has dramatically increased in recent years, many of these resources are isolated and distributed in diverse websites and databases. This hinders the discovery and overall usage of online educational resources. By using linking between related subsections of online textbooks as a testbed, this paper explores multiple knowledge-based content linking...
Word Sense Disambiguation (WSD) is the task of automatically choosing the correct meaning of a word in a context. Due to the importance of this task, it is considered as one of the most important and challenging problems in the field of computational linguistics and plays a crucial role in various natural language processing (NLP) applications. In this paper, we present an improved version of a recent...
Word sense disambiguation (WSD) is an essential task in computational linguistics for language understanding applications such as information retrieval, question answering, machine translation, text summarization etc. In this paper we propose an unsupervised WSD method for a Hindi sentence based on network agglomeration. First we create the sentence graph G for the given sentence. This sentence graph...
Highly expressive declarative languages, such as Datalog, are now commonly used to model the operational logic of data-intensive applications. The typical complexity of such Datalog programs, and the large volume of data that they process, call for the tracking and presentation of data provenance. Provenance information is crucial for explaining and justifying the Datalog program results. However,...
NELL (Never Ending Language Learning system) is the first system to practice the Never-Ending Machine Learning paradigm techniques. It has an inactive component to continually extend its KB: OntExt. Its main idea is to identify and add to the KB new relations which are frequently asserted in huge text data. Co-occurrence matrices are used to structure the normalized values of co-occurrence between...
Word Sense Disambiguation (WSD) is the process of selecting the correct sense for a word in a context. WSD has become a growing research area in the field of Natural Language Processing (NLP). Over the decades, lot of studies had been carried out to suggest different approaches for WSD process. A break-through in this field would have a significant impact on many relevant web-based applications, such...
To improve sharing and reusability of designing knowledge in domestic enterprises, a proposal of sharing of knowledge based on functional ontology was proposed. By using bases of knowledge of functional ontology, the mapping of structure-to-function has been realized. On basis of comprehensively understanding original functional model, through changing way of function achievement to obtain new functional...
Ontologies is playing an increasingly important role in knowledge management and the Semantic Web. The tourism information ontology is becoming a core research field in the realm of information retrieval. An ontology construction method based on Formal Concept Analysis (FCA) to extract domain ontology from unstructured text documents is proposed. Under the framework of our ontology construction method,...
The Peer-to-Peer systems (P2P) are the major technology of access upon various resources on Internet. A fundamental problem in Peer-to-Peer networks is how to locate appropriate peers efficiently to answer a specific query (Query routing). This paper proposes a semantic model in , which a query can be routed for appropriate peers instead of broadcasting or using random selection. This semantic is...
Providing ontologies for the automatic trend detection enhance the quality of trend predictions. However, in the case of dynamic and fuzzy expert knowledge like the knowledge used in trend detection, it is difficult to formalize knowledge unambiguously and in a static way. In this paper we report on our experiences in modeling and formalizing trend ontology for automatic knowledge-based trend detection...
This paper presents a system that combines two text mining techniques; information extraction and clustering. A rule-based approach is used to perform the information extraction task, based on the dependency relation between some intransitive verbs and prepositions. This relationship helps in extracting types of crime from documents within the crime domain. With regard to the clustering task, the...
Contextual retrieval is a critical technique for todaypsilas search engines in terms of facilitating queries and returning relevant information. This paper reports on the development and evaluation of a system designed to tackle some of the challenges associated with contextual information retrieval from the World Wide Web (WWW). The developed system has been designed with a view to capturing both...
An experimental prototype system was created and used to investigate how information relevant to analyst queries, and constrained by a contextual model, can be found over a large information space. Agents employing the ant model sift through documents quickly using a transductive support machine classifier and return those meeting a classifier which is constantly refined through feedback from semantic...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.