An effective approach to document retrieval via utilizing WordNet and recognizing phrases

Liu, Shuang; Liu, Fang; Yu, Clement; Meng, Weiyi

doi:10.1145/1008992.1009039

Cited by 171 publications

(135 citation statements)

References 24 publications

(14 reference statements)

Supporting

Mentioning

127

Contrasting

Unclassified

Order By: Relevance

“…That said, QE must be controlled in order to carefully choose the concepts to be added to the original query, otherwise the results can be disappointing [3][15]. In [11] and [12], the authors obtained positive results by expanding queries using WSD, but the effect of the use of WSD and QE are not quantified in isolation. In fact, even though the main objective of their study was to evaluate the performance of WSD in IR, they should have examined the accuracy of their disambiguation method in isolation, so that they could quantify its effect when used in their IR experiments.…”

Section: Findings and Discussionmentioning

confidence: 99%

Analysis of Word Sense Disambiguation-Based Information Retrieval

Guyot

Falquet

Radhouani

et al. 2009

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract.Several studies have tried to improve retrieval performances based on automatic Word Sense Disambiguation techniques. So far, most attempts have failed. We try, through this paper, to give a deep analysis of the reasons behind these failures. During our participation at the Robust WSD task at CLEF 2008, we performed experiments on monolingual (English) and bilingual (Spanish to English) collections. Our official results and a deep analysis are described below, along with our conclusions and perspectives.

show abstract

Section: Findings and Discussionmentioning

confidence: 99%

Analysis of Word Sense Disambiguation-Based Information Retrieval

Guyot

Falquet

Radhouani

et al. 2009

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…They used query expansion method to solve this problem by generating structured queries of boolean CNF which consist of term and its synonyms. In [3] authors aims at determining the correct sense of the given ambiguous word by adding additional useful terms to user original query.It focuses on phrases rather considering the individual term. Consequently, documents in response to the entered query are ranked based on matched phrases.…”

Section: Related Workmentioning

confidence: 99%

“…This problem is solved in RF approach where instead of using external resources it uses users feedback for expanding the original query [3].…”

Section: Pseudo Relevancementioning

confidence: 99%

Advances in IR Query Expansion

Singh

Ragha

2018

IJARCSSE

View full text Add to dashboard Cite

Abstract-As the internet is becoming rich with huge information, retrieving the wanted information is a huge challenge. Due to huge variation in framing a query by the individuals, matching of the terms with the document to be searched are facing many challenges. Researchers have worked on problem of identifying the correct essence of the user query by adding additional useful terms. They are currently working on this kind of Query Expansion (QE I. INTRODUCTIONIn our day to day life, fetching significant amount of data for academic, administrative and commercial purposes have increased. Therefore the need of the query is required to get some information for solving problems from which user can reach a certain conclusion. The role of the query is same like asking the question to search engine like google, yahoo, bing, etc. The query can be related to government, academic, commercial or personal from which doubts can be get cleared or suggestions with deep knowledge can be gained. In short, the query is something which comes in human mind. The search engine is designed to search for information where search results are the number of pages consisting of different forms of files. Among these pages, the aim is to get query related documents only.Information Retrieval [1] as IR is an activity of finding useful matter of an unstructured nature usually text within the large collection of documents stored on the computer which satisfies users need. The aim is to achieve query related documents only. Unstructured data is not organized in a pre-defined manner. The query given by a user to information retrieval can be ambiguous which may result in unrelated or irrelevant documents. The query given by user can be ambiguous due to various reasons like User lack of knowledge, Word with more than one sense, forming query in an inappropriate way, Vocabulary Mismatch problem(VMP) [2]. It is faced while matching a query with documents which is the central problem in IR which occurs when the term of the query doesn't match with the terms in relevant documents.Information storage and retrieval is a systematic storage of data collection which should be displayed on request. Relevance is a fundamental concept in Information Retrieval. Relevance is something which is related to the user query. There are many factors that go into an individual's selection as to whether a particular document is relevant or nonrelevant. It sounds simple but just by comparing and matching the keywords of a query with documents is not sufficient in terms of relevance and yields poor results. Thus considering all these factors one may design an algorithm to achieve more suitable results for the requested query.Section II describes the research work in the area of Query Expansion (QE). Different techniques are discussed in section III. An endeavour to compare different techniques briefly in section IV. A proposed method in section V. Section VI concludes the survey of different methods.

show abstract

“…In Natural Language Processing it is commonly argued that language semantics are mostly captured by nouns so it is common to built retrieval methods based on noun representations extracted from documents and queries (Varelas et al, 2005). WordNet is the most popular method for implementing semantic similarity (Liu et al, 2004;Seco et al, 2004;Tagalakis and Keane, 2005;Varelas et al, 2005).…”

Section: Measuring Semantic Similarity Based On Wordnetmentioning

confidence: 99%

Adaptive notifications to support knowledge sharing in close-knit virtual communities

Kleanthous

Dimitrova

2012

User Model User-Adap Inter

View full text Add to dashboard Cite

Social web-groups where people with common interests and goals communicate, share resources, and construct knowledge, are becoming a major part of today's organisational practice. Research has shown that appropriate support for effective knowledge sharing tailored to the needs of the community is paramount. This brings a new challenge to user modelling and adaptation, which requires new techniques for gaining sufficient understanding of a virtual community and identifying areas where the community may need support. The research presented here addresses this challenge presenting a novel computational approach for community-tailored support underpinned by organisational psychology and aimed at facilitating the functioning of the community as a whole (i.e. as an entity). A framework describing how key community processes -transactive memory, shared mental models, and cognitive centrality -can be utilised to derive knowledge sharing patterns from community log data is described. The framework includes two parts: (i) extraction of a community model that represents the community based on the key processes identified and (ii) identification of knowledge sharing behaviour patterns that are used to generate adaptive notifications. Although the notifications target individual members, they aim to influence individuals' behaviour in a way that can benefit the functioning of the community as a whole. A validation study has been performed to examine the effect of community-adapted notifications on individual members and on the community as a whole using a close-knit community of researchers sharing references. The study shows that notification messages can improve members' awareness and perception of how they relate to other members in the community. Interesting observations have been made about the linking between the physical and the virtual community, and how this may influence members' awareness and knowledge sharing behaviour. Broader implications for using log data to derive community models based on key community processes and generating community-adapted notifications are discussed.

show abstract

An effective approach to document retrieval via utilizing WordNet and recognizing phrases

Cited by 171 publications

References 24 publications

Analysis of Word Sense Disambiguation-Based Information Retrieval

Analysis of Word Sense Disambiguation-Based Information Retrieval

Advances in IR Query Expansion

Adaptive notifications to support knowledge sharing in close-knit virtual communities

Contact Info

Product

Resources

About