Knowledge Retrieval

Robots are man made machines which are used to accomplish the tasks. Robots are mainly used to do complex tasks and work in hazardous environment where humans are difficult to work. They are not only designed to use in hazardous environment but also in the environment where humans are performing the same task repeatedly. These are also used for cooking purpose some tasks can be completed with the interaction of both the human and robot one of such things is cooking where human should help robot in making dishes. This paper mainly focusses on Functional Object Oriented Network which is structured knowledge representation using the input output and motion nodes. Task tress are generated using the task tree FOON is produced and collections of all FOONS forms the universal FOON. Different algorithms to traverse the tree in order to get the best output are also discussed in this paper. The desired node or goal node can be achieved from the start node using the different search algorithms and comparison between them is discussed.Comment: 5 pages, 5 figure

Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

Knowledge Retrieval using Foon

Flexible task planning is still a significant challenge for robots. The inability of robots to creatively adapt their task plans to new or unforeseen challenges is largely attributable to their limited understanding of their activities and the environment. Cooking, for example, requires a person to occasionally take risks that a robot would find extremely dangerous. We may obtain manipulation sequences by employing knowledge that is drawn from numerous video sources thanks to knowledge retrieval through graph search.Comment: arXiv admin note: text overlap with arXiv:1902.01537 by other authors. text overlap with arXiv:2211.0299

Problem solving as intelligent retrieval from distributed knowledge sources

Distributed computing in intelligent systems is investigated from a different perspective. From the viewpoint that problem solving can be viewed as intelligent knowledge retrieval, the use of distributed knowledge sources in intelligent systems is proposed

Project Management Knowledge Retrieval: Project Classification

Project management knowledge contains a wide range of information that can be accumulated from theory and practice. This knowledge is not always readily available to project manager and that can leave a significant impact on project management efficiency and success. Therefore, this knowledge is necessary to store in the project management knowledge repository and then to retrieve it when necessary. To find this knowledge it is necessary to define attributes for searching relevant projects and knowledge associated with these projects. The objective of this paper is to develop a set of project classification attributes that can be used to describe project characteristics and use them in similarity definition. The project classification attributes are defined as a part of the architecture of project management knowledge retrieval. They are identified by analyzing several project management methodologies and are validated by classifying twenty two empirical information technology projects

Intelligent Knowledge Retrieval from Industrial Repositories

Actually, a large amount of information is stored in the industrial repositories. Accessing this information is complicated, and the techniques currently used in metadata and the material chosen by the user do not scale efficiently in large collections. The semantic Web provides a frame of reference that allows sharing and reusing knowledge efficiently. In our work, we present a focus for discovering information in digital repositories based on the application of expert system technologies, and we show a conceptual architecture for a semantic search engine. We used case-based reasoning methodology to create a prototype that supports efficient retrieval knowledge from digital repositories. OntoEnter is a collaborative effort that proposes a new form of interaction between users and digital enterprise repositories, where the latter are adapted to users and their surroundings

Knowledge Retrieval With Functional Object-Oriented Networks

In this experiment, three different search algorithms are implemented for the purpose of extracting a task tree from a large knowledge graph, known as the Functional Object-Oriented Network (FOON). Using a universal FOON, which contains knowledge extracted by annotating online cooking videos, and a desired goal, a task tree can be retrieved. The process of searching the universal FOON for task tree retrieval is tested using iterative deepening search and greedy best-first search with two different heuristic functions. The performance of these three algorithms is analyzed and compared. The results of the experiment show that iterative deepening performs strongly overall. However, different heuristics in an informed search proved to be beneficial for certain situations.Comment: 3 pages, 1 figur

Knowledge Retrieval Using Functional Object-Oriented Networks

Robotic agents often perform tasks that transform sets of input objects into output objects through functional motions. This work describes the FOON knowledge representation model for robotic tasks. We define the structure and key components of FOON and describe the process we followed to create our universal FOON dataset. The paper describes various search algorithms and heuristic functions we used to search for objects within the FOON. We performed multiple searches on our universal FOON using these algorithms and discussed the effectiveness of each algorithm.Comment: 4 pages, 3 figures, 3 table

Building a Document Corpus for Manufacturing Knowledge Retrieval

When faced with challenging technical problems, R&D personnel would often turn to technical papers to seek inspiration for a solution. The building of a corpus of such papers and the easy retrieval of relevant papers by the user in his query is an area that has not been systematically dealt with. This is an attempt to build such a corpus for manufacturing R&D personnel. Manufacturing Corpus Version 1 (MCV1) is an archive of more than 1400 relevant manufacturing engineering papers between 1998 and 2000. In this paper, the origins and motivation of building MCV1 is discussed. The innovative coding process which is specially designed for manufacturing companies will be presented. All other relevant issues, like coding policy, category codes and input documents, will be explained. Finally, two quality indicators which integrate all concerns about coding quality will be examined.Singapore-MIT Alliance (SMA