[Objective] The aim was to set up a plant digital information retrieval system.[Method] Plant digital information retrieval system was designed by combining with Microsoft Visual Basic 6.0 Enterprise Edition database ...[Objective] The aim was to set up a plant digital information retrieval system.[Method] Plant digital information retrieval system was designed by combining with Microsoft Visual Basic 6.0 Enterprise Edition database management system and Structure Query Language.[Result] The system realized electronic management and retrieval of local plant information.The key words of retrieval included family,genus,formal name,Chinese name,Latin,morphological characteristics,habitat,collection people,collection places,and protect class and so on.[Conclusion] It provided reference for these problems of species identification and digital management of herbarium.展开更多
Through analyzing syntactic,semantic,pragmatic information,the retrieval system ACIS based on comprehensive information was established,which could achieve personalized information exaction to guide user s information...Through analyzing syntactic,semantic,pragmatic information,the retrieval system ACIS based on comprehensive information was established,which could achieve personalized information exaction to guide user s information retrieval.展开更多
Objective: Information visualization is the study of interactive depictions of abstract and data to strengthen the human cognition. Designing an appropriate information visualization system may be very useful techniqu...Objective: Information visualization is the study of interactive depictions of abstract and data to strengthen the human cognition. Designing an appropriate information visualization system may be very useful technique for scholars, who intent to get scientific information from digital libraries. The objective of current study was to map and visualize the key-information of dissertations in academic libraries. To achieve the aim, an information retrieval system was designed to present the interactive graphic view of dissertations’ subjects in academic. Methods: An information retrieval system was designed by information visualization toolkit that presents the related subjects of dissertations in academic libraries. In addition, the satisfaction-levels of library-users were analyzed by administrating a standard questionnaire (QUIS Questionnaire). Results: The study indicated that the designed IR system helped to provide a user-friendly environment through displaying subjective relations of dissertations, overwhelming variety of colors in displaying information. Fast and easy access to the cover-to-cover information of dissertations and user-interaction facilities are the advantages of designed IR. Analysis of data furthermore indicated that the users’ satisfaction from the system was from medium to high grade. Conclusion: Designing the IR-system revealed an excessive influence on users’ satisfaction;therefore, proposing such systems for employing in academic libraries is very suitable and its implementation is necessary.展开更多
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 ...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.展开更多
We cleveloped a high-speed information retrieval system. The system hased on the IXP 2800 is one of the dedicute device. The velocity of the information retrieval is 6.8 Gb/s. The protocol support Telnet, FTP, SMTP, P...We cleveloped a high-speed information retrieval system. The system hased on the IXP 2800 is one of the dedicute device. The velocity of the information retrieval is 6.8 Gb/s. The protocol support Telnet, FTP, SMTP, POP3 etc. various networks protocols. The information retrieval supports the key word and the natural language process. This paper explains the hardware system, software system and the index of the performance. Key words network processor - IXP2800 - information retrieval - IXA CLC number TP 309 Foundation item: Supported by the National Natural Science Foundation of China (69873016 & 69972017) and the National High Technology Development Program of China (863-301-06-1)Biography: SHI Shu-dong (1963-), male, Ph. D. candidate, research direction: network & information security.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
Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and...Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.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
Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of dat...Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of data-driven operation management,intelligent analysis,and mining is urgently required.To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation,maintenance experience,and knowledge by rule and line,a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology.Based on the processing flow of the operating data of the power distribution system,a technical framework of neural information retrieval is established.Combined with the natural graph characteristics of the power distribution system,a unified graph data structure and a data fusion method of data access,data complement,and multi-source data are constructed.Further,a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed.The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set.The model is verified on the operating section of the power distribution system of a provincial grid area.The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.展开更多
Query expansion with thesaurus is one of the useful techniques in modern information retrieval (IR). In this paper, a method of query expansion for Chinese IR by using a decaying co-occurrence model is proposed and re...Query expansion with thesaurus is one of the useful techniques in modern information retrieval (IR). In this paper, a method of query expansion for Chinese IR by using a decaying co-occurrence model is proposed and realized. The model is an extension of the traditional co-occurrence model by adding a decaying factor that decreases the mutual information when the distance between the terms increases. Experimental results on TREC-9 collections show this query expansion method results in significant improvements over the IR without query expansion.展开更多
A concept-based approach is expected to resolve the word sense ambiguities in information retrieval and apply the semantic importance of the concepts, instead of the term frequency, to representing the contents of a d...A concept-based approach is expected to resolve the word sense ambiguities in information retrieval and apply the semantic importance of the concepts, instead of the term frequency, to representing the contents of a document. Consequently, a formalized document framework is proposed. The document framework is used to express the meaning of a document with the concepts which are expressed by high semantic importance. The framework consists of two parts： the ＂domain＂ information and the ＂situation ＆ background＂ information of a document. A document-extracting algorithm and a two-stage smoothing method are also proposed. The quantification of the similarity between the query and the document framework depends on the smoothing method. The experiments on the TREC6 collection demonstrate the feasibility and effectiveness of the proposed approach in information retrieval tasks. The average recall level precision of the model using the proposed approach is about 10% higher than that of traditional ones.展开更多
How to deal with the imprecise information retrieval has become more and more important in the present information society. An efficient and effective method of information retrieval based on multi tuple rough set is...How to deal with the imprecise information retrieval has become more and more important in the present information society. An efficient and effective method of information retrieval based on multi tuple rough set is discussed in this paper. The new approach is considered as a generalization of the original rough set model for flexible information retrieval. The imprecise query results can be obtained by multi tuple approximations.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
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
A kind of single linked lists named aggregative chain is introduced to the algorithm, thus improving the architecture of FP tree. The new FP tree is a one-way tree and only the pointers that point its parent at each n...A kind of single linked lists named aggregative chain is introduced to the algorithm, thus improving the architecture of FP tree. The new FP tree is a one-way tree and only the pointers that point its parent at each node are kept. Route information of different nodes in a same item are compressed into aggregative chains so that the frequent patterns will be produced in aggregative chains without generating node links and conditional pattern bases. An example of Web key words retrieval is given to analyze and verify the frequent pattern algorithm in this paper.展开更多
A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of key...A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.展开更多
This letter presents a new discriminative model for Information Retrieval (IR), referred to as Ordinal Regression Model (ORM). ORM is different from most existing models in that it views IR as ordinal regression probl...This letter presents a new discriminative model for Information Retrieval (IR), referred to as Ordinal Regression Model (ORM). ORM is different from most existing models in that it views IR as ordinal regression problem (i.e. ranking problem) instead of binary classification. It is noted that the task of IR is to rank documents according to the user information needed, so IR can be viewed as ordinal regression problem. Two parameter learning algorithms for ORM are presented. One is a perceptron-based algorithm. The other is the ranking Support Vector Machine (SVM). The effec- tiveness of the proposed approach has been evaluated on the task of ad hoc retrieval using three English Text REtrieval Conference (TREC) sets and two Chinese TREC sets. Results show that ORM sig- nificantly outperforms the state-of-the-art language model approaches and OKAPI system in all test sets; and it is more appropriate to view IR as ordinal regression other than binary classification.展开更多
The major problem of the most current approaches of information models lies in that individual words provide unreliable evidence about the content of the texts. When the document is short, e.g. only the abstract is av...The major problem of the most current approaches of information models lies in that individual words provide unreliable evidence about the content of the texts. When the document is short, e.g. only the abstract is available, the word-use variability problem will have substantial impact on the Information Retrieval （IR） performance. To solve the problem, a new technology to short document retrieval named Reference Document Model （RDM） is put forward in this letter. RDM gets the statistical semantic of the query/document by pseudo feedback both for the query and document from reference documents. The contributions of this model are three-fold： （1） Pseudo feedback both for the query and the document; （2） Building the query model and the document model from reference documents; （3） Flexible indexing units, which can be ally linguistic elements such as documents, paragraphs, sentences, n-grams, term or character. For short document retrieval, RDM achieves significant improvements over the classical probabilistic models on the task of ad hoc retrieval on Text REtrieval Conference （TREC） test sets. Results also show that the shorter the document, the better the RDM performance.展开更多
To eliminate the mismatch between words of relevant documents and user's query and more seriousnegative effects it has on the performance of information retrieval,a method of query expansion on the ba-sis of new t...To eliminate the mismatch between words of relevant documents and user's query and more seriousnegative effects it has on the performance of information retrieval,a method of query expansion on the ba-sis of new terms co-occurrence representation was put forward by analyzing the process of producingquery.The expansion terms were selected according to their correlation to the whole query.At the sametime,the position information between terms were considered.The experimental result on test retrievalconference(TREC)data collection shows that the method proposed in the paper has made an improve-ment of 5%～19% all the time than the language modeling method without expansion.Compared to thepopular approach of query expansion,pseudo feedback,the precision of the proposed method is competi-tive.展开更多
基金Supported by Inner Mongolia Natural Science Fund(20080404MS0507)National Natural Science Fund(30660150)+1 种基金Education Ministry Higher Education School Science Innovation Project Major Program Cultivation Fund Program(707014)Inner Mongolia Natural Scientific Fund Major Program(200607010501)~~
文摘[Objective] The aim was to set up a plant digital information retrieval system.[Method] Plant digital information retrieval system was designed by combining with Microsoft Visual Basic 6.0 Enterprise Edition database management system and Structure Query Language.[Result] The system realized electronic management and retrieval of local plant information.The key words of retrieval included family,genus,formal name,Chinese name,Latin,morphological characteristics,habitat,collection people,collection places,and protect class and so on.[Conclusion] It provided reference for these problems of species identification and digital management of herbarium.
基金Supported by the National Natural Science Foundation of China(60575034)Science Foundation of Guangxi Provincial Education Department(200708LX322)~~
文摘Through analyzing syntactic,semantic,pragmatic information,the retrieval system ACIS based on comprehensive information was established,which could achieve personalized information exaction to guide user s information retrieval.
文摘Objective: Information visualization is the study of interactive depictions of abstract and data to strengthen the human cognition. Designing an appropriate information visualization system may be very useful technique for scholars, who intent to get scientific information from digital libraries. The objective of current study was to map and visualize the key-information of dissertations in academic libraries. To achieve the aim, an information retrieval system was designed to present the interactive graphic view of dissertations’ subjects in academic. Methods: An information retrieval system was designed by information visualization toolkit that presents the related subjects of dissertations in academic libraries. In addition, the satisfaction-levels of library-users were analyzed by administrating a standard questionnaire (QUIS Questionnaire). Results: The study indicated that the designed IR system helped to provide a user-friendly environment through displaying subjective relations of dissertations, overwhelming variety of colors in displaying information. Fast and easy access to the cover-to-cover information of dissertations and user-interaction facilities are the advantages of designed IR. Analysis of data furthermore indicated that the users’ satisfaction from the system was from medium to high grade. Conclusion: Designing the IR-system revealed an excessive influence on users’ satisfaction;therefore, proposing such systems for employing in academic libraries is very suitable and its implementation is necessary.
基金Supported by the National Natural Science Foundation of China(90104005)the Natural science Foundation of Hubei Province and the Hong Kong Poly-technic University under the grant G-YD63
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.
文摘We cleveloped a high-speed information retrieval system. The system hased on the IXP 2800 is one of the dedicute device. The velocity of the information retrieval is 6.8 Gb/s. The protocol support Telnet, FTP, SMTP, POP3 etc. various networks protocols. The information retrieval supports the key word and the natural language process. This paper explains the hardware system, software system and the index of the performance. Key words network processor - IXP2800 - information retrieval - IXA CLC number TP 309 Foundation item: Supported by the National Natural Science Foundation of China (69873016 & 69972017) and the National High Technology Development Program of China (863-301-06-1)Biography: SHI Shu-dong (1963-), male, Ph. D. candidate, research direction: network & information security.
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 Innovation Fund for Medical Sciences of the Chinese Academy of Medical Sciences(2021-I2M-1-033)the National Key Research and Development Program of China(2022YFF0711900).
文摘Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.
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 Key R&D Program of China(2020YFB0905900).
文摘Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of data-driven operation management,intelligent analysis,and mining is urgently required.To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation,maintenance experience,and knowledge by rule and line,a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology.Based on the processing flow of the operating data of the power distribution system,a technical framework of neural information retrieval is established.Combined with the natural graph characteristics of the power distribution system,a unified graph data structure and a data fusion method of data access,data complement,and multi-source data are constructed.Further,a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed.The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set.The model is verified on the operating section of the power distribution system of a provincial grid area.The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.
文摘Query expansion with thesaurus is one of the useful techniques in modern information retrieval (IR). In this paper, a method of query expansion for Chinese IR by using a decaying co-occurrence model is proposed and realized. The model is an extension of the traditional co-occurrence model by adding a decaying factor that decreases the mutual information when the distance between the terms increases. Experimental results on TREC-9 collections show this query expansion method results in significant improvements over the IR without query expansion.
基金The National Basic Research Program of China(973Program)(No.2004CB318104),the Knowledge Innovation Pro-gram of Chinese Academy of Sciences (No.13CX04).
文摘A concept-based approach is expected to resolve the word sense ambiguities in information retrieval and apply the semantic importance of the concepts, instead of the term frequency, to representing the contents of a document. Consequently, a formalized document framework is proposed. The document framework is used to express the meaning of a document with the concepts which are expressed by high semantic importance. The framework consists of two parts： the ＂domain＂ information and the ＂situation ＆ background＂ information of a document. A document-extracting algorithm and a two-stage smoothing method are also proposed. The quantification of the similarity between the query and the document framework depends on the smoothing method. The experiments on the TREC6 collection demonstrate the feasibility and effectiveness of the proposed approach in information retrieval tasks. The average recall level precision of the model using the proposed approach is about 10% higher than that of traditional ones.
文摘How to deal with the imprecise information retrieval has become more and more important in the present information society. An efficient and effective method of information retrieval based on multi tuple rough set is discussed in this paper. The new approach is considered as a generalization of the original rough set model for flexible information retrieval. The imprecise query results can be obtained by multi tuple approximations.
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Supported by the Natural Science Foundation ofLiaoning Province (20042020)
文摘A kind of single linked lists named aggregative chain is introduced to the algorithm, thus improving the architecture of FP tree. The new FP tree is a one-way tree and only the pointers that point its parent at each node are kept. Route information of different nodes in a same item are compressed into aggregative chains so that the frequent patterns will be produced in aggregative chains without generating node links and conditional pattern bases. An example of Web key words retrieval is given to analyze and verify the frequent pattern algorithm in this paper.
文摘A hybrid model that is based on the Combination of keywords and concept was put forward. The hybrid model is built on vector space model and probabilistic reasoning network. It not only can exert the advantages of keywords retrieval and concept retrieval but also can compensate for their shortcomings. Their parameters can be adjusted according to different usage in order to accept the best information retrieval result, and it has been proved by our experiments.
基金Supported by the High Technology Research and Devel-opment Program of China (No.2006AA01Z150)the Key Project of the National Natural Science Foundation of China (No.60373101)+1 种基金the Natural Science Foundation of Heilongjiang Province (No.F2007-14)the Project of Heilongjiang Outstanding Young University Teacher (No. 1151G037).
文摘This letter presents a new discriminative model for Information Retrieval (IR), referred to as Ordinal Regression Model (ORM). ORM is different from most existing models in that it views IR as ordinal regression problem (i.e. ranking problem) instead of binary classification. It is noted that the task of IR is to rank documents according to the user information needed, so IR can be viewed as ordinal regression problem. Two parameter learning algorithms for ORM are presented. One is a perceptron-based algorithm. The other is the ranking Support Vector Machine (SVM). The effec- tiveness of the proposed approach has been evaluated on the task of ad hoc retrieval using three English Text REtrieval Conference (TREC) sets and two Chinese TREC sets. Results show that ORM sig- nificantly outperforms the state-of-the-art language model approaches and OKAPI system in all test sets; and it is more appropriate to view IR as ordinal regression other than binary classification.
基金Supported by the Funds of Heilongjiang Outstanding Young Teacher (1151G037).
文摘The major problem of the most current approaches of information models lies in that individual words provide unreliable evidence about the content of the texts. When the document is short, e.g. only the abstract is available, the word-use variability problem will have substantial impact on the Information Retrieval （IR） performance. To solve the problem, a new technology to short document retrieval named Reference Document Model （RDM） is put forward in this letter. RDM gets the statistical semantic of the query/document by pseudo feedback both for the query and document from reference documents. The contributions of this model are three-fold： （1） Pseudo feedback both for the query and the document; （2） Building the query model and the document model from reference documents; （3） Flexible indexing units, which can be ally linguistic elements such as documents, paragraphs, sentences, n-grams, term or character. For short document retrieval, RDM achieves significant improvements over the classical probabilistic models on the task of ad hoc retrieval on Text REtrieval Conference （TREC） test sets. Results also show that the shorter the document, the better the RDM performance.
基金the High Technology Research and Development Program of China(No.2006AA01Z150)the National Natural Science Foundation of China(No.60435020)
文摘To eliminate the mismatch between words of relevant documents and user's query and more seriousnegative effects it has on the performance of information retrieval,a method of query expansion on the ba-sis of new terms co-occurrence representation was put forward by analyzing the process of producingquery.The expansion terms were selected according to their correlation to the whole query.At the sametime,the position information between terms were considered.The experimental result on test retrievalconference(TREC)data collection shows that the method proposed in the paper has made an improve-ment of 5%～19% all the time than the language modeling method without expansion.Compared to thepopular approach of query expansion,pseudo feedback,the precision of the proposed method is competi-tive.
