Putting Search in Context: Using Dynamically-Weighted Information Fusion to Improve Search Results
11 Apr 2011-pp 66-71
TL;DR: USearch, an agent-based context-aware search system that fuses context information to improve search results is introduced here.
Abstract: The modern world is a highly connected one. Many diverse populations are utilizing the web as a learning tool. Often, the quest for information on the Internet begins by entering a search string into a search engine such as Google or Bing and then sifting through the multitude of results searching for information relevant to the user in his or her current situation. The web along with search engine technology has enabled people to have access to a wealth of information previously unavailable or out of reach of the average person. While the search process seems intuitive -- enter a search string and "presto!" results are retrieved -- constructing appropriate search strings and filtering results can be a complicated process, difficult for even the sophisticated user. Thus, the real issue that remains is perfecting the search tools and their underlying algorithms so that this search process will be simplified and personalized for the average user. As search engines are a typical user's interface to the World Wide Web, aiding the average user who possesses minimal query development skills in his or her quest for relevant, personalized results is an important goal. In addition, it is easy to see that mobile computing is also becoming pervasive in today's society. Use of personal digital assistants is common, and even cellular phones are Internet enabled. This trend is likely to continue, and this means that the user's context is likely to vary significantly as he or she uses these tools. Why not take advantage of context information to make the user's mobile computing experience simpler? USearch, an agent-based context-aware search system that fuses context information to improve search results is introduced here.
Citations
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30 Jun 2012
TL;DR: A Hindi search engine is presented in which three models for query enhancement are described based on lexical variance, user context and combination of both techniques.
Abstract: The traditional search engine have shortcoming that they retrieve irrelevant information. Query expansion with relevant words increases the performance of search engines, but finding and using the relevant words is an open problem. This paper presents a Hindi search engine in which we describe three models for query enhancement. They are based on lexical variance, user context and combination of both techniques.
6 citations
Patent•
IBM1
TL;DR: In this paper, each query term of the query is analyzed to determine whether it corresponds to either a domain keyword or a formula designator, and each formula term associated with the formula designators is mapped to a domain keywords.
Abstract: Aspects of the present invention provide a tool for retrieving data in response to a query in any format. In an embodiment, each query term of the query is analyzed to determine whether it corresponds to either a domain keyword or a formula designator. If a formula designator is retrieved, each formula term associated with the formula designator is mapped to a domain keyword. Each of the domain keywords, the formula designators, and the mapped formula terms are boosted. A dataset is searched using a structured search query that includes all boosted terms, as well as any remaining query terms that do not correspond to one of the boosted terms.
1 citations
TL;DR: A provenance model is proposed which uses both content based and trust based factors in identifying trusted search results andinferences performed over the provenance matrix leads to trust score which is then utilized to remove near-duplicates and retrieve trusting search results.
Abstract: During web search, we often end up with untrusted, duplicates and near duplicate search results which dilutes the focus of search query. Factors that may influence the trust of web search results shall be referred to as ’Provenance’. Provenance is basically the information about the history of data. In this paper, we propose a provenance model which uses both content based and trust based factors in identifying trusted search results. The novelty of our idea lies in attempting to construct a provenance matrix which encompasses 6 factors (who, where, when, what, why, how) related to the search results. Inferences performed over the provenance matrix leads to trust score which is then utilized to remove near-duplicates and retrieve trusted search results.
1 citations
Cites background from "Putting Search in Context: Using Dy..."
...Query Expansion is stated in Nicole Anderson [6] work ....
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01 Sep 2012
TL;DR: Experimental results shown that the approach to personalized query expansion based on an expert system for mobile search can significantly improve user's experience and has much better performance in precision than that of the existing public search engines.
Abstract: -Compared with the traditional PC-based web search, the mobile search needs more personalization. An approach to personalized query expansion based on an expert system for mobile search is proposed. Our main work concentrates on the algorithms of query expansion. First, environmental information obtained by a mobile device and query terms submitted by a user are formatted into the specific format. Then these treated elements are sent to an expert system to match with the rules. Finally, according to the matched rules, the additional keywords are appended to the query terms so as to catch on the user's search intention. Experimental results shown that the approach we proposed can significantly improve user's experience and has much better performance in precision than that of the existing public search engines.
References
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27 Sep 1999
TL;DR: Some of the research challenges in understanding context and in developing context-aware applications are discussed, which are increasingly important in the fields of handheld and ubiquitous computing, where the user?s context is changing rapidly.
Abstract: When humans talk with humans, they are able to use implicit situational information, or context, to increase the conversational bandwidth. Unfortunately, this ability to convey ideas does not transfer well to humans interacting with computers. In traditional interactive computing, users have an impoverished mechanism for providing input to computers. By improving the computer’s access to context, we increase the richness of communication in human-computer interaction and make it possible to produce more useful computational services. The use of context is increasingly important in the fields of handheld and ubiquitous computing, where the user?s context is changing rapidly. In this panel, we want to discuss some of the research challenges in understanding context and in developing context-aware applications.
4,842 citations
"Putting Search in Context: Using Dy..." refers background in this paper
...[1] define context as any information that can be used to characterize the situation of an entity....
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TL;DR: An active map service (AMS) is described that supports context-aware computing by providing clients with information about located-objects and how those objects change over time and how that information is disseminated to its clients.
Abstract: The article describes an active map service (AMS) that supports context-aware computing by providing clients with information about located-objects and how those objects change over time. The authors focus on the communication issues of disseminating information from an active map server to its clients, and in particular, address how to deal with various overload situations that can occur. Simple unicast callbacks to interested clients work well enough if only a few located-objects are moving at any given time and only a few clients wish to know about any given move. However, if many people are moving about in the same region and many clients are interested in their motion, then the AMS may experience overload due to the quadratic nature of the communications involved. This overload affects both the server as well as any slow communications links being used. Mobile distributed computing enables users to interact with many different mobile and stationary computers over the course of the day. Navigating a mobile environment can be aided by active maps that describe the location and characteristics of objects within some region as they change over time. >
1,787 citations
"Putting Search in Context: Using Dy..." refers background in this paper
...[2] were one of the first groups to identify context-aware computing as an important aspect of mobile computing....
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Journal Article•
TL;DR: A new conceptual paradigm for performing search in context is presented, that largely automates the search process, providing even non-professional users with highly relevant results.
Abstract: Keyword-based search engines are in widespread use today as a popular means for Web-based information retrieval Although such systems seem deceptively simple, a considerable amount of skill is required in order to satisfy non-trivial information needs This paper presents a new conceptual paradigm for performing search in context, that largely automates the search process, providing even non-professional users with highly relevant results This paradigm is implemented in practice in the IntelliZap system, where search is initiated from a text query marked by the user in a document she views, and is guided by the text surrounding the marked query in that document (“the context”) The context-driven information retrieval process involves semantic keyword extraction and clustering to automatically generate new, augmented queries The latter are submitted to a host of general and domain-specific search engines Search results are then semantically reranked, using context Experimental results testify that using context to guide search, effectively offers even inexperienced users an advanced search tool on the Web
1,615 citations
"Putting Search in Context: Using Dy..." refers background in this paper
...Software agents are essentially software components with specific traits such as proactiveness, reactiveness, autonomy, and sociability [5]....
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01 Apr 2001
TL;DR: A new conceptual paradigm for performing search in context is presented, that largely automates the search process, providing even non-professional users with highly relevant results.
Abstract: Keyword-based search engines are in widespread use today as a popular means for Web-based information retrieval. Although such systems seem deceptively simple, a considerable amount of skill is required in order to satisfy non-trivial information needs. This paper presents a new conceptual paradigm for performing search in context, that largely automates the search process, providing even non-professional users with highly relevant results. This paradigm is implemented in practice in the IntelliZap system, where search is initiated from a text query marked by the user in a document she views, and is guided by the text surrounding the marked query in that document (“the context”). The context-driven information retrieval process involves semantic keyword extraction and clustering to automatically generate new, augmented queries. The latter are submitted to a host of general and domain-specific search engines. Search results are then semantically reranked, using context. Experimental results testify that using context to guide search, effectively offers even inexperienced users an advanced search tool on the Web.
922 citations
"Putting Search in Context: Using Dy..." refers background in this paper
...Software agents are essentially software components with specific traits such as proactiveness, reactiveness, autonomy, and sociability [ 5 ]....
[...]
01 Jun 2000
TL;DR: It is found that while successful search performance requires the combination of the two types of expertise, specific strategies directly related to Web experience or domain knowledge can be identified.
Abstract: Searching for relevant information on the World Wide Web is often a laborious and frustrating task for casual and experienced users. To help improve searching on the Web based on a better understanding of user characteristics, we investigate what types of knowledge are relevant for Web-based information seeking, and which knowledge structures and strategies are involved. Two experimental studies are presented, which address these questions from different angles and with different methodologies. In the first experiment, 12 established Internet experts are first interviewed about search strategies and then perform a series of realistic search tasks on the World Wide Web. From this study a model of information seeking on the World Wide Web is derived and then tested in a second study. In the second experiment two types of potentially relevant types of knowledge are compared directly. Effects of Web experience and domain-specific background knowledge are investigated with a series of search tasks in an economics-related domain (introduction of the Euro currency). We find differential and combined effects of both Web experience and domain knowledge: while successful search performance requires the combination of the two types of expertise, specific strategies directly related to Web experience or domain knowledge can be identified.
721 citations
"Putting Search in Context: Using Dy..." refers background in this paper
...This seems reasonable as studies have shown that 80% of web searchers view no more than the top 10 results returned by search engines [9]....
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