In this paper, we employ genetic algorithms to solve the migration problem (MP). We propose a new encoding scheme to represent trees, which is composed of two parts: the pre-ordered traversal sequence of tree vertices...In this paper, we employ genetic algorithms to solve the migration problem (MP). We propose a new encoding scheme to represent trees, which is composed of two parts: the pre-ordered traversal sequence of tree vertices and the children number sequence of corresponding tree vertices. The proposed encoding scheme has the advantages of simplicity for encoding and decoding, ease for GA operations, and better equilibrium between exploration and exploitation. It is also adaptive in that, with few restrictions on the length of code, it can be freely lengthened or shortened according to the characteristics of the problem space. Furthermore, the encoding scheme is highly applicable to the degree-constrained minimum spanning tree problem because it also contains the degree information of each node. The simulation results demonstrate the higher performance of our algorithm, with fast convergence to the optima or sub-optima on various problem sizes. Comparing with the binary string encoding of vertices, when the problem size is large, our algorithm runs remarkably faster with comparable search capability. Key words distributed information retrieval - mobile agents - migration problem - genetic algorithms CLC number TP 301. 6 Foundation item: Supported by the National Natural Science Foundation of China (90104005), the Natural Science Foundation of Hubei Province and the Hong Kong Polytechnic University under the grant G-YD63Biography: He Yan-xiang (1952-), male, Professor, research direction: distributed and parallel processing, multi-agent systems, data mining and e-business.展开更多
Ontology is the progression of interpreting the conceptions of the information domain for an assembly of handlers.Familiarizing ontology as information retrieval(IR)aids in augmenting the searching effects of user-req...Ontology is the progression of interpreting the conceptions of the information domain for an assembly of handlers.Familiarizing ontology as information retrieval(IR)aids in augmenting the searching effects of user-required relevant information.The crux of conventional keyword matching-related IR utilizes advanced algorithms for recovering facts from the Internet,mapping the connection between keywords and information,and categorizing the retrieval outcomes.The prevailing procedures for IR consume considerable time,and they could not recover information proficiently.In this study,through applying a modified neuro-fuzzy algorithm(MNFA),the IR time is mitigated,and the retrieval accuracy is enhanced for trouncing the above-stated downsides.The proposed method encompasses three phases:i)development of a crop ontology,ii)implementation of the IR system,and iii)processing of user query.In the initial phase,a crop ontology is developed and evaluated by gathering crop information.In the next phase,a hash tree is constructed using closed frequent patterns(CFPs),and MNFA is used to train the database.In the last phase,for a specified user query,CFP is calculated,and similarity assessment results are retrieved using the database.The performance of the proposed system is measured and compared with that of existing techniques.Experimental results demonstrate that the proposed MNFA has an accuracy of 92.77% for simple queries and 91.45% for complex queries.展开更多
A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search wha...A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search what they need. The system consists of four main components: interface agent, information retrieval agent, broker agent and learning agent. They collaborate to implement system functions. The agents apply learning mechanisms based on an improved ID3 algorithm.展开更多
With the rapid increment of the information on the web, traditional information retrieval based on the keywords is far from user＇s satisfaction in recall and precision. In order to improve the recall ratio and the pr...With the rapid increment of the information on the web, traditional information retrieval based on the keywords is far from user＇s satisfaction in recall and precision. In order to improve the recall ratio and the precision radio of IR engine in the vegetables e-commerce, an information retrieval model based on the vegetables e-commerce ontology is presented in this paper, vegetables e-commerce ontology was constructed by gathering and the analyzing vegetables e-commerce domain information on the web. The vegetables e-commerce ontology is composed of some kinds of vegetable classes and hierarchy relationship of vegetables classes. In the process of information retrieval, domain ontology helps to index information and information inference. An ontology-based information retrieval model is implemented, and which has more functions than the keyword-based web information retrieval engines. The experiment results show that the recall ratio and the precision ratio of ontology-based information retrieval model are higher than that of the information retrieval engine based on keyword at a certain extent.展开更多
The drastic growth of coastal observation sensors results in copious data that provide weather information.The intricacies in sensor-generated big data are heterogeneity and interpretation,driving high-end Information...The drastic growth of coastal observation sensors results in copious data that provide weather information.The intricacies in sensor-generated big data are heterogeneity and interpretation,driving high-end Information Retrieval(IR)systems.The Semantic Web(SW)can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval.This paper focuses on exploiting the SWbase systemto provide interoperability through ontologies by combining the data concepts with ontology classes.This paper presents a 4-phase weather data model:data processing,ontology creation,SW processing,and query engine.The developed Oceanographic Weather Ontology helps to enhance data analysis,discovery,IR,and decision making.In addition to that,it also evaluates the developed ontology with other state-of-the-art ontologies.The proposed ontology’s quality has improved by 39.28%in terms of completeness,and structural complexity has decreased by 45.29%,11%and 37.7%in Precision and Accuracy.Indian Meteorological Satellite INSAT-3D’s ocean data is a typical example of testing the proposed model.The experimental result shows the effectiveness of the proposed data model and its advantages in machine understanding and IR.展开更多
Based on the comparison between ontology and thesaurus, and the analysis of an ontology-based Information Retrieval （IR） model, the potential advantages that ontology may contribute to IR are analyzed. Then a genera...Based on the comparison between ontology and thesaurus, and the analysis of an ontology-based Information Retrieval （IR） model, the potential advantages that ontology may contribute to IR are analyzed. Then a general architecture of ontology-based Information Retrieval System （IRS） and the approach of constructing it are presented. Based on the researches, the role of ontology in IR is summarized from four aspects and a typical system called Textpresso is analyzed. Finally, a conclusion is drawn that utilizing ontology is the trend of IR and can really improve the IRS.展开更多
This paper described an ontology based multi agent knowledge process made (MAKM) which is one of multi agents systems (MAS) and uses semantic network to describe agents to help to locate relative agents distributed in...This paper described an ontology based multi agent knowledge process made (MAKM) which is one of multi agents systems (MAS) and uses semantic network to describe agents to help to locate relative agents distributed in the workgroup. In MAKM, an agent is the entity to implement the distributed task processing and to access the information or knowledge. Knowledge query manipulation language (KQML) is adapted to realize the communication among agents. So using the MAKM mode, different knowledge and information on the medical domain could be organized and utilized efficiently when a collaborative task is implemented on the web.展开更多
This paper presents a new integrated information retrieval support system （IIRSS） which can help Web search engines retrieve cross-lingual information from hereto geneous resources stored in multi-databases in Intra...This paper presents a new integrated information retrieval support system （IIRSS） which can help Web search engines retrieve cross-lingual information from hereto geneous resources stored in multi-databases in Intranet. The IIRSS, with a three-layer architecture, can cooperate with other application servers running in Intranet. By using intelligent agents to collect information and to create indexes on the-fly, using an access control strategy to confine a user to browsing those accessible documents for him/her through a single portal, and using a new cross-lingual translation tool to help the search engine retrieve documents, the new system provides controllable information access with different authorizations, personalized services, and real-time information retrieval.展开更多
In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according t...In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according to its characteristics. Domain ontology of product-design is estab- lished and the semantic annotation technology is used to connect the design knowledge and ontolo- gy. A new semantic annotation format is developed and semantic information of the design knowl- edge is enriched by making use of ontology. On that basis a retrieval algorithm is designed for semantic retrieval. Finally, this approach is used in a knowledge management system for military-vehi- cle design and its effectiveness and feasibility are validated. Results show that the recall ratio and the precision ratio of knowledge retrieval are improved greatly and users＇ requirements in semantic retrieval are satisfied.展开更多
Daily newspapers publish a tremendous amount of information disseminated through the Internet.Freely available and easily accessible large online repositories are not indexed and are in an un-processable format.The ma...Daily newspapers publish a tremendous amount of information disseminated through the Internet.Freely available and easily accessible large online repositories are not indexed and are in an un-processable format.The major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and indexed.There is no method to reuse the online news images because of the unavailability of standardized benchmark corpora,especially for South Asian languages.The corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and specifically for the Urdu language.Lack of indexing,primarily semantic indexing of the daily news items,makes news items impracticable for any querying.Moreover,the most straightforward search facility does not support these unindexed news resources.Our study addresses this gap by associating and marking the newspaper images with one of the widely spoken but under-resourced languages,i.e.,Urdu.The present work proposed a method to build a benchmark corpus of news in image form by introducing a web crawler.The corpus is then semantically linked and annotated with daily news items.Two techniques are proposed for image annotation,free annotation and fixed cross examination annotation.The second technique got higher accuracy.Build news ontology in protégéusing OntologyWeb Language(OWL)language and indexed the annotations under it.The application is also built and linked with protégéso that the readers and journalists have an interface to query the news items directly.Similarly,news items linked together will provide complete coverage and bring together different opinions at a single location for readers to do the analysis themselves.展开更多
This paper describes a project that has created a Topic Map search tool for a mathematics educational database containing articles from the journal For the Learning of Mathematics.The resulting website enables users t...This paper describes a project that has created a Topic Map search tool for a mathematics educational database containing articles from the journal For the Learning of Mathematics.The resulting website enables users to retrieve research articles based on a variety of topics such as mathematics classification,research methods,educational objectives,in addition to traditional bibliographic information.展开更多
文摘In this paper, we employ genetic algorithms to solve the migration problem (MP). We propose a new encoding scheme to represent trees, which is composed of two parts: the pre-ordered traversal sequence of tree vertices and the children number sequence of corresponding tree vertices. The proposed encoding scheme has the advantages of simplicity for encoding and decoding, ease for GA operations, and better equilibrium between exploration and exploitation. It is also adaptive in that, with few restrictions on the length of code, it can be freely lengthened or shortened according to the characteristics of the problem space. Furthermore, the encoding scheme is highly applicable to the degree-constrained minimum spanning tree problem because it also contains the degree information of each node. The simulation results demonstrate the higher performance of our algorithm, with fast convergence to the optima or sub-optima on various problem sizes. Comparing with the binary string encoding of vertices, when the problem size is large, our algorithm runs remarkably faster with comparable search capability. Key words distributed information retrieval - mobile agents - migration problem - genetic algorithms CLC number TP 301. 6 Foundation item: Supported by the National Natural Science Foundation of China (90104005), the Natural Science Foundation of Hubei Province and the Hong Kong Polytechnic University under the grant G-YD63Biography: He Yan-xiang (1952-), male, Professor, research direction: distributed and parallel processing, multi-agent systems, data mining and e-business.
文摘Ontology is the progression of interpreting the conceptions of the information domain for an assembly of handlers.Familiarizing ontology as information retrieval(IR)aids in augmenting the searching effects of user-required relevant information.The crux of conventional keyword matching-related IR utilizes advanced algorithms for recovering facts from the Internet,mapping the connection between keywords and information,and categorizing the retrieval outcomes.The prevailing procedures for IR consume considerable time,and they could not recover information proficiently.In this study,through applying a modified neuro-fuzzy algorithm(MNFA),the IR time is mitigated,and the retrieval accuracy is enhanced for trouncing the above-stated downsides.The proposed method encompasses three phases:i)development of a crop ontology,ii)implementation of the IR system,and iii)processing of user query.In the initial phase,a crop ontology is developed and evaluated by gathering crop information.In the next phase,a hash tree is constructed using closed frequent patterns(CFPs),and MNFA is used to train the database.In the last phase,for a specified user query,CFP is calculated,and similarity assessment results are retrieved using the database.The performance of the proposed system is measured and compared with that of existing techniques.Experimental results demonstrate that the proposed MNFA has an accuracy of 92.77% for simple queries and 91.45% for complex queries.
文摘A new information search model is reported and the design and implementation of a system based on intelligent agent is presented. The system is an assistant information retrieval system which helps users to search what they need. The system consists of four main components: interface agent, information retrieval agent, broker agent and learning agent. They collaborate to implement system functions. The agents apply learning mechanisms based on an improved ID3 algorithm.
基金supported by the National High Technology Research and Development Program of China(2006AA10Z239)
文摘With the rapid increment of the information on the web, traditional information retrieval based on the keywords is far from user＇s satisfaction in recall and precision. In order to improve the recall ratio and the precision radio of IR engine in the vegetables e-commerce, an information retrieval model based on the vegetables e-commerce ontology is presented in this paper, vegetables e-commerce ontology was constructed by gathering and the analyzing vegetables e-commerce domain information on the web. The vegetables e-commerce ontology is composed of some kinds of vegetable classes and hierarchy relationship of vegetables classes. In the process of information retrieval, domain ontology helps to index information and information inference. An ontology-based information retrieval model is implemented, and which has more functions than the keyword-based web information retrieval engines. The experiment results show that the recall ratio and the precision ratio of ontology-based information retrieval model are higher than that of the information retrieval engine based on keyword at a certain extent.
基金This work is financially supported by the Ministry of Earth Science(MoES),Government of India,(Grant.No.MoES/36/OOIS/Extra/45/2015),URL:https://www.moes.gov.in。
文摘The drastic growth of coastal observation sensors results in copious data that provide weather information.The intricacies in sensor-generated big data are heterogeneity and interpretation,driving high-end Information Retrieval(IR)systems.The Semantic Web(SW)can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval.This paper focuses on exploiting the SWbase systemto provide interoperability through ontologies by combining the data concepts with ontology classes.This paper presents a 4-phase weather data model:data processing,ontology creation,SW processing,and query engine.The developed Oceanographic Weather Ontology helps to enhance data analysis,discovery,IR,and decision making.In addition to that,it also evaluates the developed ontology with other state-of-the-art ontologies.The proposed ontology’s quality has improved by 39.28%in terms of completeness,and structural complexity has decreased by 45.29%,11%and 37.7%in Precision and Accuracy.Indian Meteorological Satellite INSAT-3D’s ocean data is a typical example of testing the proposed model.The experimental result shows the effectiveness of the proposed data model and its advantages in machine understanding and IR.
文摘Based on the comparison between ontology and thesaurus, and the analysis of an ontology-based Information Retrieval （IR） model, the potential advantages that ontology may contribute to IR are analyzed. Then a general architecture of ontology-based Information Retrieval System （IRS） and the approach of constructing it are presented. Based on the researches, the role of ontology in IR is summarized from four aspects and a typical system called Textpresso is analyzed. Finally, a conclusion is drawn that utilizing ontology is the trend of IR and can really improve the IRS.
基金National Natural Science Foundation of China (No. 6993 10 10 )
文摘This paper described an ontology based multi agent knowledge process made (MAKM) which is one of multi agents systems (MAS) and uses semantic network to describe agents to help to locate relative agents distributed in the workgroup. In MAKM, an agent is the entity to implement the distributed task processing and to access the information or knowledge. Knowledge query manipulation language (KQML) is adapted to realize the communication among agents. So using the MAKM mode, different knowledge and information on the medical domain could be organized and utilized efficiently when a collaborative task is implemented on the web.
基金Supported by the National Natural Science Foun-dation of China (60173010)
文摘This paper presents a new integrated information retrieval support system （IIRSS） which can help Web search engines retrieve cross-lingual information from hereto geneous resources stored in multi-databases in Intranet. The IIRSS, with a three-layer architecture, can cooperate with other application servers running in Intranet. By using intelligent agents to collect information and to create indexes on the-fly, using an access control strategy to confine a user to browsing those accessible documents for him/her through a single portal, and using a new cross-lingual translation tool to help the search engine retrieve documents, the new system provides controllable information access with different authorizations, personalized services, and real-time information retrieval.
基金Supported by the National Defence Research Foundation(41234)
文摘In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according to its characteristics. Domain ontology of product-design is estab- lished and the semantic annotation technology is used to connect the design knowledge and ontolo- gy. A new semantic annotation format is developed and semantic information of the design knowl- edge is enriched by making use of ontology. On that basis a retrieval algorithm is designed for semantic retrieval. Finally, this approach is used in a knowledge management system for military-vehi- cle design and its effectiveness and feasibility are validated. Results show that the recall ratio and the precision ratio of knowledge retrieval are improved greatly and users＇ requirements in semantic retrieval are satisfied.
基金King Saud University through Researchers Supporting Project number(RSP-2021/387),King Saud University,Riyadh,Saudi Arabia.
文摘Daily newspapers publish a tremendous amount of information disseminated through the Internet.Freely available and easily accessible large online repositories are not indexed and are in an un-processable format.The major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and indexed.There is no method to reuse the online news images because of the unavailability of standardized benchmark corpora,especially for South Asian languages.The corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and specifically for the Urdu language.Lack of indexing,primarily semantic indexing of the daily news items,makes news items impracticable for any querying.Moreover,the most straightforward search facility does not support these unindexed news resources.Our study addresses this gap by associating and marking the newspaper images with one of the widely spoken but under-resourced languages,i.e.,Urdu.The present work proposed a method to build a benchmark corpus of news in image form by introducing a web crawler.The corpus is then semantically linked and annotated with daily news items.Two techniques are proposed for image annotation,free annotation and fixed cross examination annotation.The second technique got higher accuracy.Build news ontology in protégéusing OntologyWeb Language(OWL)language and indexed the annotations under it.The application is also built and linked with protégéso that the readers and journalists have an interface to query the news items directly.Similarly,news items linked together will provide complete coverage and bring together different opinions at a single location for readers to do the analysis themselves.
文摘This paper describes a project that has created a Topic Map search tool for a mathematics educational database containing articles from the journal For the Learning of Mathematics.The resulting website enables users to retrieve research articles based on a variety of topics such as mathematics classification,research methods,educational objectives,in addition to traditional bibliographic information.
