A semi-supervised incremental algorithm to automatically formulate topical queries

Lorenzetti, Carlos M.; Maguitman, Ana Gabriela

doi:10.1016/j.ins.2009.01.029

Cited by 24 publications

(16 citation statements)

References 32 publications

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“…A topic descriptor is defined as a term that often occurs in documents relevant to the topic while a topic discriminator is a term that occurs only in relevant documents. Topic descriptors and discriminators can be learned based on the user topical context and incrementally collected documents [23,24].…”

Section: Context Extraction and Modelingmentioning

confidence: 99%

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Searching in the Context of a Task: A Review of Methods and Tools

Maguitman¹

2018

CLEIej

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Contextual information extracted from the user task can help to better target retrieval to task-relevant content. In particular, topical context can be exploited to identify the subject of the information needs, contributing to reduce the information overload problem. A great number of methods exist to extract raw context data and contextual interaction patterns from the user task and to model this information using higher-level representations. Context can then be used as a source for automatic query generation, or as a means to refine or disambiguate user-generated queries. It can also be used to filter and rank results as well as to select domain-specific search engines with better capabilities to satisfy specific information requests. This article reviews methods that have been applied to deal with the problem of reflecting the current and long-term interests of a user in the search process. It discusses major difficulties encountered in the research area of context-based information retrieval and presents an overview of tools proposed since the mid-nineties to deal with the problem of context-based search.

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Section: Context Extraction and Modelingmentioning

confidence: 99%

“…Topical context can be used for query refinement by applying a semi-supervised version of the classical relevance feedback method [24]. Relevance feedback, proposed by Rocchio [57], is a query refinement mechanism used to tune queries based on the relevance assessments of the query's results.…”

Section: Context For Query Refinementmentioning

confidence: 99%

Searching in the Context of a Task: A Review of Methods and Tools

Maguitman¹

2018

CLEIej

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“…Context-based search in Twitter is an instance of context-based search in general [6]. The task of context-based search could be applied in many different situations.…”

Section: Context-based Search For Social Mediamentioning

confidence: 99%

“…DECIDE 2.0 aims at extending the current state of the art of web 2.0 technologies by integrating existing social media tools with argumentation and context-aware technologies. Following its aim, DECIDE 2.0 combines context-based search [6] and argumentation [7] in a collaborative system for managing (retrieving and publishing) service-and policy-related information in social media tools used by governments. Therefore, DECIDE 2.0 contributes to a more enhanced set of Government 2.0 tools.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

Integrating argumentation technologies and context-based search for intelligent processing of citizens' opinion in social media

Chesñevar

Maguitman

Estévez³

et al. 2012

Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance

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Nowadays, governments are adopting Web 2.0 technologies for interacting with citizens, empowering them to share their views, react to issues of their concern and form opinion. In particular, social media play an important role in this context, due to their widespread use. For governments, a major technical challenge is the lack of automated intelligent tools for processing citizens' opinion in government social media. At the same time, during the last decade, argumentation theory has consolidated itself in Artificial Intelligence as a new paradigm for modeling common sense reasoning, with application in several areas, such as legal reasoning, multiagent systems, and decision support systems, among others. This paper outlines an argument-based approach for overcoming such challenge, combined with context-based information retrieval. Our ultimate aim is to combine contextbased search and argumentation in a collaborative framework for managing (retrieving and publishing) service-and policy-related information in government-use social media tools.

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“…Meanwhile, conceptual graph is an appropriate representing method for this purpose. A survey on existing research activities in this field reveals various applications for query expansion such as : using query expansion in graph-based approach for query-focused multi-document summarization [4], syntactically-based query reformulation technique for information retrieval [5], semi-supervised incremental algorithm to automatically formulate topical queries [6] and simplifying syntactic and semantic parsing of NLP-based queries in advanced application domains by using ontologies [7].…”

Section: Existing Approaches To Query Expansionmentioning

confidence: 99%

A Framework for Query Expansion Based on Viewpoint-Oriented Manipulation of the Related Concepts

Badie

Mahmoudi

Ghaderi

2010

2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation

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Although search engines are quite useful for obtaining information from the World Wide Web, users still have problems obtaining the most relevant information when processing their web queries. Different methods exist for query expansion with various levels of success. A major point in query expansion techniques is to consider the relations existing between the query terms as a means for retrieving more relevant web pages. Therefore, the more comprehensible these relations are observed, the more relevance can be expected for the retrieved web pages. Taking this point into account, in this paper, a framework is represented for query expansion based on viewpoint-oriented manipulation of the related query terms. Comparison between the relevant retrieved documents, on proposed queries with Google results, illustrate how more relevant results are obtained in the situations where the very viewpoints type relations existing between the query terms are clearly detectable and in the meantime no semantic relation may at the first look exists between the query terms. In this paper, we have made use of two approaches to retrieval issue, out of which one is based on information fusion while the other is grounded on collaboration of the results in a selective way.

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A semi-supervised incremental algorithm to automatically formulate topical queries

Cited by 24 publications

References 32 publications

Searching in the Context of a Task: A Review of Methods and Tools

Searching in the Context of a Task: A Review of Methods and Tools

Integrating argumentation technologies and context-based search for intelligent processing of citizens' opinion in social media

A Framework for Query Expansion Based on Viewpoint-Oriented Manipulation of the Related Concepts

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