The Experts below are selected from a list of 3879 Experts worldwide ranked by ideXlab platform
Maria Fasli - One of the best experts on this subject based on the ideXlab platform.
-
adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
International ACM SIGIR Conference on Research and Development in Information Retrieval, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
-
SIGIR - Adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
Anne De Roeck - One of the best experts on this subject based on the ideXlab platform.
-
adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
International ACM SIGIR Conference on Research and Development in Information Retrieval, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
-
SIGIR - Adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
-
building and applying a Concept Hierarchy representation of a user profile
International ACM SIGIR Conference on Research and Development in Information Retrieval, 2003Co-Authors: Nikolaos Nanas, Victoria Uren, Anne De RoeckAbstract:Term dependence is a natural consequence of language use. Its successful representation has been a long standing goal for Information Retrieval research. We present a methodology for the construction of a Concept Hierarchy that takes into account the three basic dimensions of term dependence. We also introduce a document evaluation function that allows the use of the Concept Hierarchy as a user profile for Information Filtering. Initial experimental results indicate that this is a promising approach for incorporating term dependence in the way documents are filtered.
-
SIGIR - Building and applying a Concept Hierarchy representation of a user profile
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval - SIGIR '03, 2003Co-Authors: Nikolaos Nanas, Victoria Uren, Anne De RoeckAbstract:Term dependence is a natural consequence of language use. Its successful representation has been a long standing goal for Information Retrieval research. We present a methodology for the construction of a Concept Hierarchy that takes into account the three basic dimensions of term dependence. We also introduce a document evaluation function that allows the use of the Concept Hierarchy as a user profile for Information Filtering. Initial experimental results indicate that this is a promising approach for incorporating term dependence in the way documents are filtered.
Ibrahim Adeyanju - One of the best experts on this subject based on the ideXlab platform.
-
adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
International ACM SIGIR Conference on Research and Development in Information Retrieval, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
-
SIGIR - Adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
Dawei Song - One of the best experts on this subject based on the ideXlab platform.
-
automatic update of ontology Concept Hierarchy with new entity insertion and new Concept generation based on semantic measurement
International Conference Software and Computer Applications, 2018Co-Authors: Yinghui Wang, Bo Wang, Dawei SongAbstract:Ontology, as a representation of shared Conceptualization for variety of specific domains, is the core of the semantic web. Concept Hierarchy is one of the most popular backbones of ontology which organizes the Concepts according to hyponymy relationships, and stores massive entities as the instances of the Concepts. An open Concept Hierarchy, e.g., Wikipedia, always needs to be constantly updated by adding new entities and Concepts. In this paper, we propose an automatic solution for ontology update by inserting new entities and generating new Concepts for Concept Hierarchy. The method only requires very limited information of new entity, i.e., the attributes of each entity. The solution is based on a hybrid strategy synthesizing the benefits from the structure of the Concept tree and the content of the attributes. The content of the attributes is used to measure the similarity between an entity and a Concept. The structure of the Concept tree is used to determine which Concepts need to be measured. During similarity measurement, the solution also synthesizes the statistical and rule-based factors. The effectiveness of the proposed method is verified by the experiments extending the Chinese and English Wikipedia Concept Hierarchy with new entities and Concepts.
-
adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
International ACM SIGIR Conference on Research and Development in Information Retrieval, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
-
SIGIR - Adaptation of the Concept Hierarchy model with search logs for query recommendation on intranets
Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval - SIGIR '12, 2012Co-Authors: Ibrahim Adeyanju, Anne De Roeck, Dawei Song, Mdyaa Albakour, Udo Kruschwitz, Maria FasliAbstract:A Concept Hierarchy created from a document collection can be used for query recommendation on Intranets by ranking terms according to the strength of their links to the query within the Hierarchy. A major limitation is that this model produces the same recommendations for identical queries and rebuilding it from scratch periodically can be extremely inefficient due to the high computational costs. We propose to adapt the model by incorporating query refinements from search logs. Our intuition is that the Concept Hierarchy built from the collection and the search logs provide complementary Conceptual views on the same search domain, and their integration should continually improve the effectiveness of recommended terms. Two adaptation approaches using query logs with and without click information are compared. We evaluate the Concept Hierarchy models (static and adapted versions) built from the Intranet collections of two academic institutions and compare them with a state-of-the-art log-based query recommender, the Query Flow Graph, built from the same logs. Our adaptive model significantly outperforms its static version and the query flow graph when tested over a period of time on data (documents and search logs) from two institutions' Intranets.
Somya Srivastava - One of the best experts on this subject based on the ideXlab platform.
-
extracting diverse patterns with unbalanced Concept Hierarchy
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2014Co-Authors: Kumara M Swamy, Krishna P Reddy, Somya SrivastavaAbstract:The process of frequent pattern extraction finds interesting information about the association among the items in a transactional database. The notion of support is employed to extract the frequent patterns. Normally, in a given domain, a set of items can be grouped into a category and a pattern may contain the items which belong to multiple categories. In several applications, it may be useful to distinguish between the pattern having items belonging to multiple categories and the pattern having items belonging to one or a few categories. The notion of diversity captures the extent the items in the pattern belong to multiple categories. The items and the categories form a Concept Hierarchy. In the literature, an approach has been proposed to rank the patterns by considering the balanced Concept Hierarchy. In a real life scenario, the Concept hierarchies are normally unbalanced. In this paper, we propose a general approach to calculate the rank based on the diversity, called drank, by considering the unbalanced Concept Hierarchy. The experiment results show that the patterns ordered based on drank are different from the patterns ordered based on support, and the proposed approach could assign the drank to different kinds of unbalanced patterns.
-
PAKDD (1) - Extracting Diverse Patterns with Unbalanced Concept Hierarchy
Advances in Knowledge Discovery and Data Mining, 2014Co-Authors: M. Kumara Swamy, P. Krishna Reddy, Somya SrivastavaAbstract:The process of frequent pattern extraction finds interesting information about the association among the items in a transactional database. The notion of support is employed to extract the frequent patterns. Normally, in a given domain, a set of items can be grouped into a category and a pattern may contain the items which belong to multiple categories. In several applications, it may be useful to distinguish between the pattern having items belonging to multiple categories and the pattern having items belonging to one or a few categories. The notion of diversity captures the extent the items in the pattern belong to multiple categories. The items and the categories form a Concept Hierarchy. In the literature, an approach has been proposed to rank the patterns by considering the balanced Concept Hierarchy. In a real life scenario, the Concept hierarchies are normally unbalanced. In this paper, we propose a general approach to calculate the rank based on the diversity, called drank, by considering the unbalanced Concept Hierarchy. The experiment results show that the patterns ordered based on drank are different from the patterns ordered based on support, and the proposed approach could assign the drank to different kinds of unbalanced patterns.