A Taxonomy and Survey of Semantic Approaches for Query Expansion
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A Query Suggestion Method Combining TF-IDF and Jaccard Coefficient for Interactive Web Search
www.sciedu.ca/air Artificial Intelligence Research 2015, Vol. 4, No. 2 ORIGINAL RESEARCH A query suggestion method combining TF-IDF and Jaccard Coefficient for interactive web search Suthira Plansangket ,∗ John Q Gan School of Computer Science and Electronic Engineering, University of Essex, United Kingdom Received: May 10, 2015 Accepted: July 27, 2015 Online Published: August 6, 2015 DOI: 10.5430/air.v4n2p119 URL: http://dx.doi.org/10.5430/air.v4n2p119 Abstract This paper proposes a query suggestion method combining two ranked retrieval methods: TF-IDF and Jaccard coefficient. Four performance criteria plus user evaluation have been adopted to evaluate this combined method in terms of ranking and relevance from different perspectives. Two experiments have been conducted using carefully designed eighty test queries which are related to eight topics. One experiment aims to evaluate the quality of the query suggestions generated by the proposed method, and the other aims to evaluate the improvement of the relevance of retuned documents in interactive web search by using the query suggestions so as to evaluate the effectiveness of the developed method. The experimental results show that the method developed in this paper is the best method for query suggestion among the methods evaluated, significantly outperforming the most popularly used TF-IDF method. In addition, the query suggestions generated by the proposed method significantly improve the relevance of returned documents in interactive web search in terms of increasing the precision or the number of highly relevant documents. Key Words: Query suggestion, Query expansion, Information retrieval, Search engine, Performance evaluation 1 Introduction a cold-start problem. -
Representing and Reasoning About Semantic Conflicts in Heterogeneous Information Systems
Representing and Reasoning about Semantic Conflicts in Heterogeneous Information Systems Cheng Hian Goh CISL WP# 97-01 January 1997 The Sloan School of Management Massachusetts Institute of Technology Cambridge, MA 02142 Representing and Reasoning about Semantic Conflicts in Heterogeneous Information Systems by Cheng Hian Goh Submitted to the Sloan School of Management on Dec 5, 1996, in partial fulfillment of the requirements for the degree of Doctor of Philosophy Abstract The context INterchange (COIN) strategy [Sciore et al., 1994, Siegel and Madnick, 1991] presents a novel perspective for mediated data access in which semantic con- flicts among heterogeneous systems are not identified a priori, but are detected and reconciled by a Context Mediator through comparison of contexts associated with any two systems engaged in data exchange. In this Thesis, we present a formal character- ization and reconstruction of this strategy in a COIN framework, based on a deductive object-oriented data model and language called COIN. The COIN framework provides a logical formalism for representing data semantics in distinct contexts. We show that this presents a well-founded basis for reasoning about semantic disparities in heterogeneous systems. In addition, it combines the best features of loose- and tight- coupling approaches in defining an integration strategy that is scalable, extensible and accessible. These latter features are made possible by teasing apart context knowledge from the underlying schemas whenever feasible, by enabling sources and receivers to remain loosely-coupled to one another, and by sustaining an infrastructure for data integration. The feasibility and features of this approach have been demonstrated in a prototype implementation which provides mediated access to traditional database systems (e.g., Oracle databases) as well as semi-structured data (e.g., Web-sites). -
Concept-Based Interactive Query Expansion ∗
Concept-Based Interactive Query Expansion ∗ Bruno M. Fonseca12 Paulo Golgher2 Bruno Pôssas12 [email protected] [email protected] [email protected] Berthier Ribeiro-Neto1 2 Nivio Ziviani1 [email protected] [email protected] ABSTRACT back, web searching. Despite the recent advances in search quality, the fast increase in the size of the Web collection has introduced new challenges for 1. INTRODUCTION Web ranking algorithms. In fact, there are still many situations in The Web is an innovation that has modified the way we learn, which the users are presented with imprecise or very poor results. work and live. The novelty lies not only on the freedom to publish, One of the key difficulties is the fact that users usually submit very but also in the almost universal communication facilities. It marks short and ambiguous queries, and they do not fully specify their in- formation needs. That is, it is necessary to improve the query for- the beginning of a new era, of a new society, started by what we mation process if better answers are to be provided. In this work we may call the information revolution. In these new times, the volume of information that can be ac- propose a novel concept-based query expansion technique, which cessed at low cost and high convenience is mind boggling. To illus- allows disambiguating queries submitted to search engines. The trate, Google1 advertised indexing more than 8 billion Web pages concepts are extracted by analyzing and locating cycles in a special type of query relations graph. This is a directed graph built from in 2004. -
A Semantic Query Method for Deep Web∗
Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) A Semantic Query Method for Deep Web∗ Jiang Hao**,Liu Wen-ju, Lu Li-li School of Computer Science and Engineering Southeast University Nanjing, Jiangsu Province 210096, China [email protected] Abstract—Based on the idea of "functionality-centric", this Web environment. paper proposes a complete set of oriented semantic query methods for Deep Web, builds up the relevant software II. RELEVANT RESEARCH WORK architecture, provides a new method for full use of Deep Web Lots of relevant researches have been done at home data resources in semantic web environment through and abroad in recent years, including following describing the establishment of the semantic environment, implementations: re-writing the SPARQL-to-SQL query, semantic packaging of semantic query result, and the architecture of semantic query A. Web data integration services. It mainly includes two methods in traditional Web data Keywords-Deep Web; semantic query; SPARQ and RDF integration and ontology-based semantic integration. The view traditional Web data integration is typical for WISE-Integrator[4] and MetaQuerier[5] developed by I. INTRODUCTION American scholar with the idea of schema extracting of the Deep Web query interface, constructing the integrated The Deep Web, an important part of the current Web interface, implementing data query and integration through information, refers to the hidden information in the Web the meta-queries. While Ontology-based semantic database. With the continuous development of computer integration is mainly concentrated on the Deep Web depth, networks, the reality of how to use effectively the Deep Web describing the semantics of Web data sources through local data resources becomes a hot issue. -
A Survey of Geospatial Semantic Web for Cultural Heritage
heritage Review A Survey of Geospatial Semantic Web for Cultural Heritage Ikrom Nishanbaev 1,* , Erik Champion 1 and David A. McMeekin 2 1 School of Media, Creative Arts, and Social Inquiry, Curtin University, Perth, WA 6845, Australia; [email protected] 2 School of Earth and Planetary Sciences, Curtin University, Perth, WA 6845, Australia; [email protected] * Correspondence: [email protected] Received: 23 April 2019; Accepted: 16 May 2019; Published: 20 May 2019 Abstract: The amount of digital cultural heritage data produced by cultural heritage institutions is growing rapidly. Digital cultural heritage repositories have therefore become an efficient and effective way to disseminate and exploit digital cultural heritage data. However, many digital cultural heritage repositories worldwide share technical challenges such as data integration and interoperability among national and regional digital cultural heritage repositories. The result is dispersed and poorly-linked cultured heritage data, backed by non-standardized search interfaces, which thwart users’ attempts to contextualize information from distributed repositories. A recently introduced geospatial semantic web is being adopted by a great many new and existing digital cultural heritage repositories to overcome these challenges. However, no one has yet conducted a conceptual survey of the geospatial semantic web concepts for a cultural heritage audience. A conceptual survey of these concepts pertinent to the cultural heritage field is, therefore, needed. Such a survey equips cultural heritage professionals and practitioners with an overview of all the necessary tools, and free and open source semantic web and geospatial semantic web platforms that can be used to implement geospatial semantic web-based cultural heritage repositories. -
Federated Query Processing for the Semantic Web
Departamento de Inteligencia Artificial Facultad de Informatica´ Federated Query Processing for the Semantic Web A thesis submitted for the degree of PhD Thesis Author: Msc. Carlos Buil-Aranda Advisor: Dr. Oscar Corcho Garc´ıa January 2012 ii Tribunal nombrado por el Sr. Rector Magfco. de la Universidad Politecnica´ de Madrid, el d´ıa...............de.............................de 20.... Presidente : Vocal : Vocal : Vocal : Secretario : Suplente : Suplente : Realizado el acto de defensa y lectura de la Tesis el d´ıa..........de......................de 20...... en la E.T.S.I. /Facultad...................................................... Calificacion´ .................................................................................. EL PRESIDENTE LOS VOCALES EL SECRETARIO iii Abstract The recent years have witnessed a constant growth in the amount of RDF data available on the Web. This growth is largely based on the increasing rate of data publication on the Web by different actors such governments, life science researchers or geographical institutes. RDF data generation is mainly done by converting already existing legacy data resources into RDF (e.g. converting data stored in relational databases into RDF), but also by creating that RDF data directly (e.g. sensors). These RDF data are normally exposed by means of Linked Data-enabled URIs and SPARQL endpoints. Given the sustained growth that we are experiencing in the number of SPARQL endpoints available, the need to be able to send federated SPARQL queries across them has also grown. Tools for accessing sets of RDF data repositories are starting to appear, differing between them on the way in which they allow users to access these data (allowing users to specify directly what RDF data set they want to query, or making this process transparent to them). -
Xu: an Automated Query Expansion and Optimization Tool
Xu: An Automated Query Expansion and Optimization Tool Morgan Gallant Haruna Isah Farhana Zulkernine Shahzad Khan School of Computing School of Computing School of Computing Gnowit Inc. Queen’s University Queen’s University Queen’s University Ottawa, ON, Canada Kingston, ON, Canada Kingston, ON, Canada Kingston, ON, Canada [email protected] [email protected] [email protected] [email protected] Abstract— The exponential growth of information on the A core issue in IR and search applications is the evaluation Internet is a big challenge for information retrieval systems of search results. The emphasis is on users and their towards generating relevant results. Novel approaches are information needs. The users of an IR system such as a search required to reformat or expand user queries to generate a engine, are the ultimate judges of the quality of the results [2]. satisfactory response and increase recall and precision. Query There are many reasons why a search result may not meet user expansion (QE) is a technique to broaden users’ queries by expectations. Sometimes the query expression may be too introducing additional tokens or phrases based on some short to dictate what the user is looking for or may not be well semantic similarity metrics. The tradeoff is the added formulated [5]. In most cases, the user's original query is not computational complexity to find semantically similar words sufficient to retrieve the information that the user is looking and a possible increase in noise in information retrieval. Despite several research efforts on this topic, QE has not yet been for [6]. -
EAGLE—A Scalable Query Processing Engine for Linked Sensor Data †
sensors Article EAGLE—A Scalable Query Processing Engine for Linked Sensor Data † Hoan Nguyen Mau Quoc 1,* , Martin Serrano 1, Han Mau Nguyen 2, John G. Breslin 3 and Danh Le-Phuoc 4 1 Insight Centre for Data Analytics, National University of Ireland Galway, H91 TK33 Galway, Ireland; [email protected] 2 Information Technology Department, Hue University, Hue 530000, Vietnam; [email protected] 3 Confirm Centre for Smart Manufacturing and Insight Centre for Data Analytics, National University of Ireland Galway, H91 TK33 Galway, Ireland; [email protected] 4 Open Distributed Systems, Technical University of Berlin, 10587 Berlin, Germany; [email protected] * Correspondence: [email protected] † This paper is an extension version of the conference paper: Nguyen Mau Quoc, H; Le Phuoc, D.: “An elastic and scalable spatiotemporal query processing for linked sensor data”, in proceedings of the 11th International Conference on Semantic Systems, Vienna, Austria, 16–17 September 2015. Received: 22 July 2019; Accepted: 4 October 2019; Published: 9 October 2019 Abstract: Recently, many approaches have been proposed to manage sensor data using semantic web technologies for effective heterogeneous data integration. However, our empirical observations revealed that these solutions primarily focused on semantic relationships and unfortunately paid less attention to spatio–temporal correlations. Most semantic approaches do not have spatio–temporal support. Some of them have attempted to provide full spatio–temporal support, but have poor performance for complex spatio–temporal aggregate queries. In addition, while the volume of sensor data is rapidly growing, the challenge of querying and managing the massive volumes of data generated by sensing devices still remains unsolved. -
Query Expansion with Locally-Trained Word Embeddings
Query Expansion with Locally-Trained Word Embeddings Fernando Diaz Bhaskar Mitra Nick Craswell Microsoft Microsoft Microsoft [email protected] [email protected] [email protected] Abstract trained using local windows, risks captur- ing only coarse representations of those top- Continuous space word embeddings ics dominant in the corpus. While a par- have received a great deal of atten- ticular embedding may be appropriate for a tion in the natural language processing specific word within a sentence-length con- and machine learning communities for text globally, it may be entirely inappropri- their ability to model term similarity ate within a specific topic. Gale et al. re- and other relationships. We study the fer to this as the ‘one sense per discourse’ use of term relatedness in the context property (Gale et al., 1992). Previous work of query expansion for ad hoc informa- by Yarowsky demonstrates that this property tion retrieval. We demonstrate that can be successfully combined with informa- word embeddings such as word2vec and tion from nearby terms for word sense dis- GloVe, when trained globally, under- ambiguation (Yarowsky, 1995). Our work ex- perform corpus and query specific em- tends this approach to word2vec-style training beddings for retrieval tasks. These re- in the context word similarity. sults suggest that other tasks benefit- For many tasks that require topic-specific ing from global embeddings may also linguistic analysis, we argue that topic-specific benefit from local embeddings. representations should outperform global rep- resentations. Indeed, it is difficult to imagine 1 Introduction a natural language processing task that would Continuous space embeddings such as not benefit from an understanding of the local word2vec (Mikolov et al., 2013b) or GloVe topical structure. -
Semantic Web Technologies and Data Management
Semantic Web Technologies and Data Management Li Ma, Jing Mei, Yue Pan Krishna Kulkarni Achille Fokoue, Anand Ranganathan IBM China Research Laboratory IBM Software Group IBM Watson Research Center Bei Jing 100094, China San Jose, CA 95141-1003, USA New York 10598, USA Introduction The Semantic Web aims to build a common framework that allows data to be shared and reused across applications, enterprises, and community boundaries. It proposes to use RDF as a flexible data model and use ontology to represent data semantics. Currently, relational models and XML tree models are widely used to represent structured and semi-structured data. But they offer limited means to capture the semantics of data. An XML Schema defines a syntax-valid XML document and has no formal semantics, and an ER model can capture data semantics well but it is hard for end-users to use them when the ER model is transformed into a physical database model on which user queries are evaluated. RDFS and OWL ontologies can effectively capture data semantics and enable semantic query and matching, as well as efficient data integration. The following example illustrates the unique value of semantic web technologies for data management. Figure 1. An example of ontology based data management In Figure 1, we have two tables in a relational database. One stores some basic information of several companies, and another one describes shareholding relationship among these companies. Sometimes, users want to issue such a query “find Company EDOX’s all direct and indirect shareholders which are from Europe and are IT company”. Based on the data stored in the database, existing RDBMSes cannot represent and answer the above query. -
A New Query Expansion Method Based on Query Logs Mining1
International Journal on Asian Language Processing, 19 (1): 1-12 1 A new query expansion method based on query logs mining 1 Zhu Kunpeng, Wang Xiaolong, Liu Yuanchao School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China Email:{kpzhu, wangxl, ycliu}@insun.hit.edu.cn Abstract: Query expansion has long been suggested as an effective way to improve the performance of information retrieval systems by adding additional relevant terms to the original queries. However, most previous research has been limited in extracting new terms from a subset of relevant documents, but has not exploited the information about user interactions. In this paper, we proposed a method for automatic query expansion based on user interactions recorded in query logs. The central idea is to extract correlations among queries by analyzing the common documents the users selected for them, and the expanded terms only come from the associated queries more than the relevant documents. In particular, we argue that queries should be dealt with in different ways according to their ambiguity degrees, which can be calculated from the log information. We verify this method in a large scale query logs collection and the experimental results show that the method makes good use of the knowledge of user interactions, and it can remarkably improve search performance. Keywords: Query expansion, log mining, information retrieval, search engine, 1. Introduction With the rapid growth of information on the World Wide Web, more and more users need search engine technology to help them exploit such an extremely valuable resource. Although many search engine systems have been successfully deployed, the current search systems are still far from optimal because of using simple keywords to search and rank relevant documents. -
Query Expansion Techniques
Query Expansion techniques Ashish Kankaria Indian Institute of Technology Bombay, Mumbai [email protected] 1. NEED OF QUERY EXPANSION • Creating a dictionary of expansion terms for each terms, The Information Retrieval system described above works and then looking up in the dictionary for expansion very well if the user is able to convey his information need in form of query. But query is seldom complete. The query 2. EXTERNAL RESOURCE BASED QUERY provided by the user is often unstructured and incomplete. An incomplete query hinders a search engine from satisfy- EXPANSION ing the user’s information need. In practice we need some In these approaches, the query is expanded using some ex- representation which can correctly and more importantly ternal resource like WordNet, lexical dictionaries or the- completely express the user’s information need. saurus.These dictionaries are built manually which contain mappings of the terms to their relevant terms. There tech- Figure 1 explains the need of query expansion. Consider niques involve look up in such resources and adding the re- an input query “Sachin Tendulkar”. As a search engine de- lated terms to query. Following are some of external re- veloper we would expect that user wants documents related source based query expansion techniques. [5] to cricketer Sachin Tendulkar. Consider our corpus has 2 documents. First document is an informative page about 2.1 Thesaurus based expansion Sachin Tendulkar which contains the query terms where as A thesaurus is a data structure that lists words grouped to- second document is an blog on Tendulkar which has various gether according to similarity of meaning (containing syn- adjectives related to Sachin Tendulkar like master blaster or onyms and sometimes antonyms), in contrast to a dictio- God of cricket but does not have query terms.