Web Search---Your Way

Glover, Eric; Lawrence, Steve; Gordon, Michael D.; Birmingham, William P.; Giles, C. Lee

doi:10.1145/501317.501319

Cited by 83 publications

(47 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The query choice is calculated by analysing the probabilies of which queries from the log are most likely to follow the initial query based on past usage patterns. Similarly, Glover et al (2001) generate a set of modified queries from the initial query in their Inquirus2 system and then submit these to a selection of search engines (see Figure 3). (Glover et al, 2001) The modified queries however do not take into account semantics related to the query, as they rather attempt to broaden the search by appending terms such as "links" or "resources" for particular search types.…”

Section: Figure 1 User Profile Generation Using Odp Categoriesmentioning

confidence: 99%

“…Similarly, Glover et al (2001) generate a set of modified queries from the initial query in their Inquirus2 system and then submit these to a selection of search engines (see Figure 3). (Glover et al, 2001) The modified queries however do not take into account semantics related to the query, as they rather attempt to broaden the search by appending terms such as "links" or "resources" for particular search types. The type of words added to the queries depends on a "need category" specified by a user, which denotes a certain query intent.…”

Section: Figure 1 User Profile Generation Using Odp Categoriesmentioning

confidence: 99%

“…However, the notion of expansion strategies introduced in Glover et al (2001) has been confined to simple hardcoded rules that are applied for every user with the same query. Firstly, this leads to a scalability issue for the creation of new rules, since they each have to be created manually.…”

Section: Summary and Critiquementioning

confidence: 99%

“…Especially the user intent of a query would be of great use to a system in order to create a customised strategy for search result diversification. Currently, only the system provided by Glover et al (2001) provides a basic implementation of this feature by requiring a user to explicitly choose a query intent.…”

Section: Comparison Across Query Adaptation Techniquesmentioning

confidence: 99%

See 3 more Smart Citations

A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques

Steichen

Ashman

Wade

2012

Information Processing & Management

View full text Add to dashboard Cite

Abstract.A key driver for next generation web information retrieval systems is becoming the degree to which a user's search and presentation experience is adapted to individual user properties and contexts of use. Over the past decades, two parallel threads of personalisation research have emerged, one originating in the document space in the area of Personalised Information Retrieval (PIR) and the other arising from the hypertext space in the field of Adaptive Hypermedia (AH).PIR typically aims to bias search results towards more personally relevant information by modifying traditional document ranking algorithms. Such techniques tend to represent users with simplified personas (often based on historic interests), enabling the efficient calculation of personalised ranked lists. On the other hand, the field of Adaptive Hypermedia (AH) has addressed the challenge of biasing content retrieval and presentation by adapting towards multiple characteristics. These characteristics, more typically called personalisation "dimensions", include user goals or prior knowledge, enabling adaptive and personalised result compositions and navigations.The question arises as to whether it is possible to provide a comparison of PIR and AH, where the respective strengths and limitations can be exposed, but also where potential complementary affordances can be identified. This survey investigates the key techniques and impacts in the use of PIR and AH technology in order to identify such affordances and limitations. In particular, the techniques are analysed by examining key activities in the retrieval process, namely (i) query adaptation, (ii) adaptive retrieval and (iii) adaptive result composition and presentation. In each of these areas, the survey identifies individual strengths and limitations. Following this comparison of techniques, the paper also illustrates an example of a potential synergy in a hybridised approach, where adaptation can be tailored in different aspects of PIR and AH systems. Moreover, the concerns resulting from interdependencies and the respective tradeoffs of techniques are discussed, along with potential future directions and remaining challenges.

show abstract

Section: Figure 1 User Profile Generation Using Odp Categoriesmentioning

confidence: 99%

Section: Figure 1 User Profile Generation Using Odp Categoriesmentioning

confidence: 99%

Section: Summary and Critiquementioning

confidence: 99%

Section: Comparison Across Query Adaptation Techniquesmentioning

confidence: 99%

See 2 more Smart Citations

A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques

Steichen

Ashman

Wade

2012

Information Processing & Management

View full text Add to dashboard Cite

show abstract

“…The initial paraphrase Q 0  N is relegated to state (-LOCATION'', 8,0) since it is a -where'' question, it is 8 words in length, and contains no proper nouns.…”

Section: 6mentioning

confidence: 99%

Query Modulation For Web-Based Question Answering

Radev

Qi²,

Zheng

et al. 2008

Advances in Open Domain Question Answering

View full text Add to dashboard Cite

Abstract:The web is now becoming one of the largest information and knowledge repositories. Many large scale search engines (Google, Fast, Northern Light, etc.) have emerged to help users find information. In this paper, we study how we can effectively use these existing search engines to mine the Web and discover the -correct'' answers to factual natural language questions. We propose a probabilistic algorithm called QASM (Question Answering using Statistical Models) that learns the best query paraphrase of a natural language question. We validate our approach for both local and web search engines using questions from the TREC evaluation.

show abstract

Bibliography

2010

An Introduction to Search Engines and Web Navigation

View full text Add to dashboard Cite

Web Search---Your Way

Abstract: Improving Web searching with user preferences.

Cited by 83 publications

References 5 publications

A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques

A comparative survey of Personalised Information Retrieval and Adaptive Hypermedia techniques

Query Modulation For Web-Based Question Answering

Bibliography

Contact Info

Product

Resources

About