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This document summarizes a seminar on information literacy for computer science students presented by Maletta Payne, an emerging technologies librarian. The seminar covered how to access and search the library's databases and e-book collections, database search strategies, interlibrary loan services, and contacting the librarian for research help. Key computer science databases were listed and searching tips including using boolean operators and subject headings were provided.
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The document discusses contextualized online search and research skills. It outlines both the strengths and weaknesses of internet research, including speed, sharing information, and potential personal information leaks or incorrect information. It provides tips for effective online research such as checking sources, asking good questions, going beyond the surface, being patient, and respecting ownership. The document also lists popular search engines and describes common digital image file formats like TIFF, JPEG, GIF, PNG, and raw files.
The document provides guidance on initial steps for developing a search application, including validating the need for full-text search, identifying ideal search results, considering clustering results, and producing requirements and choosing a technology. Some key recommendations include sketching out ideal results for sample queries, determining how results should be ordered and presented, and considering if and how results could be clustered. Determining ideal results and clustering options can help drive specific requirements and the selection of an appropriate technology.
Search Solutions 2011: Successful Enterprise Search By DesignMarianne Sweeny
When your colleagues say they want Google, they don’t mean the Google Search Appliance. They mean the Google Search user experience: pervasive, expedient and delivering the information that they need. Successful enterprise search does not start with the application features, is not part of the information architecture, does not come from a controlled vocabulary and does not emerge on its own from the developers. It requires enterprise-specific data mining, enterprise-specific user-centered design and fine tuning to turn “search sucks” into search success within the firewall. This presentation looks at action items, tools and deliverables for Discovery, Planning, Design and Post Launch phases of an enterprise search deployment.
The document summarizes best practices for improving enterprise intranet search. It discusses how enterprise search differs from public web search due to more complex data, users, and information needs. It provides tips for understanding users and their search behavior through analytics, designing search interfaces that support users of all skill levels, and implementing an iterative process of testing, measuring, and improving search performance over time.
The document summarizes best practices for improving enterprise intranet search. It discusses how enterprise search differs from public web search due to more complex data, users, and information needs. It provides tips for understanding users and their search behavior through analytics, designing interfaces to support users of all skill levels, and implementing an iterative process of testing, measuring, and improving search performance over time.
This document summarizes a seminar on information literacy for computer science students presented by Maletta Payne, an emerging technologies librarian. The seminar covered how to access and search the library's databases and e-book collections, database search strategies, interlibrary loan services, and contacting the librarian for research help. Key computer science databases were listed and searching tips including using boolean operators and subject headings were provided.
The document discusses using technology in qualitative research. It describes various technologies that can be used including word processing, spreadsheets, presentation software, and qualitative data analysis (QDA) software like Ethnograph. It emphasizes that QDA software like Ethnograph helps researchers organize, code, search, and analyze large amounts of qualitative data. The document provides an overview of the basic processes involved in using QDA software to compile data, organize it through coding, and manipulate the data through searching and comparing coded segments.
The document discusses contextualized online search and research skills. It outlines both the strengths and weaknesses of internet research, including speed, sharing information, and potential personal information leaks or incorrect information. It provides tips for effective online research such as checking sources, asking good questions, going beyond the surface, being patient, and respecting ownership. The document also lists popular search engines and describes common digital image file formats like TIFF, JPEG, GIF, PNG, and raw files.
The document provides guidance on initial steps for developing a search application, including validating the need for full-text search, identifying ideal search results, considering clustering results, and producing requirements and choosing a technology. Some key recommendations include sketching out ideal results for sample queries, determining how results should be ordered and presented, and considering if and how results could be clustered. Determining ideal results and clustering options can help drive specific requirements and the selection of an appropriate technology.
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When your colleagues say they want Google, they don’t mean the Google Search Appliance. They mean the Google Search user experience: pervasive, expedient and delivering the information that they need. Successful enterprise search does not start with the application features, is not part of the information architecture, does not come from a controlled vocabulary and does not emerge on its own from the developers. It requires enterprise-specific data mining, enterprise-specific user-centered design and fine tuning to turn “search sucks” into search success within the firewall. This presentation looks at action items, tools and deliverables for Discovery, Planning, Design and Post Launch phases of an enterprise search deployment.
The document summarizes best practices for improving enterprise intranet search. It discusses how enterprise search differs from public web search due to more complex data, users, and information needs. It provides tips for understanding users and their search behavior through analytics, designing search interfaces that support users of all skill levels, and implementing an iterative process of testing, measuring, and improving search performance over time.
The document summarizes best practices for improving enterprise intranet search. It discusses how enterprise search differs from public web search due to more complex data, users, and information needs. It provides tips for understanding users and their search behavior through analytics, designing interfaces to support users of all skill levels, and implementing an iterative process of testing, measuring, and improving search performance over time.
The hunt for the perfect interface in a googlified worldnabot
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SearchLand is a talk that provides an overview of how web search engines work for beginners. It discusses that search engines do not actually search the web directly, but rather create an index of crawled web pages. The talk outlines the basic architecture of search engines, including crawling, indexing, and ranking documents. It also discusses challenges in measuring search quality and different evaluation approaches between information retrieval research and actual search engine practices. The talk concludes by noting that improving search quality requires continuous measurement and analysis.
The document summarizes a presentation about search and navigation requirements for a multimedia archive called iMMix. It discusses challenges in searching large audiovisual collections with diverse target groups. It outlines different user types and their information needs, and proposes a model with search competence and knowledge dimensions to support different search behaviors. Key points include connecting user demand to content supply through metadata, the challenges of search interfaces, and adding value through features like thesauri, keyframes and faceted search.
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InkSeine: In Situ Search for Active Note Taking
1. Ken Hinckley, Shengdong Zhao, Raman Sarin,
Patrick Baudisch, Edward Cutrell, Michael Shilman &
Desney Tan
oronto
2. In situ search for digital ink
InkSeine :
Ink +
Seine
-n: a fishing net
-v: to fish with a seine
= insanely cool
ink search!
InkSeine lets the user
fish for useful information
directly from ink notes.
Fishermen catching salmon
on the Columbia River
using a seine.
(courtesy Wikipedia)
3. Active note taking
XLibris—pen-based system for active reading
(reading + critical thinking + learning)
InkSeine combines pen-based note taking with
searching, linking, collecting & sensemaking:
5. Ink-Search-Gather
interaction pattern
Search – digging through
the file system on a tablet
is really a pain
Active note taking benefits from
low overhead access to
supporting materials & related
docs
Focus on personal search, but
support Web as well
Ink
6. Ink-Search-Gather
interaction pattern
Gather – Make it easy to
use what you find by
pulling content directly into
unstructured notes
Thumbnail hyperlinks to
documents
Clippings from documents
Queries that can be revisited later
Ink
8. In situ search
Leverage preexisting ink to initiate search
No context switch to “search app” – stay in the flow
No tedious copying of information to a “search box”
Queries as first class objects, commingled with ink notes
Flag some ink for search for later
Visible and salient search history as part of notes
Queries can be copied, pasted, moved, etc.
Interleave inking, searching & gathering
No barrier between inking / searching – note ideas while
searching, side-by-side searching, span app boundaries for
content gathering
Tightly couple queries with application content
Queries naturally persist in originating context
Easy re-visitation of prior queries
Results of queries become new content
9. Rich tradeoffs in cost
structure of sensemaking
Continuum of time cost – can defer at any point:
1 second: Capture thought “I should search on this”
5 seconds: Trigger search & see initial results list
10s: Open a document from result list, or drag result into notes
10s-30s:
Inspect details of a few results
Apply filters to results
Add a word to the query
Grab a snapshot from a short document
Correct occasional reco errors – but Tablet’s reco is amazingly good!
Longer: sufficient depth for common info needs; not mired by
last 10% of complex queries that require full featured search
tools
Scroll through longer results lists
Inspect result documents to see if they meet information needs
Sideways searches based on Title, Date, or Author of a result
16. Findings
Existing desktop search tool difficult to use
Difficult text entry
Enter and correct text
Annoying context switch and flow interruption
Switch among apps and context
17. Findings
Existing desktop search tool difficult to use
Difficult text entry
Enter and correct text
Annoying context switch and flow interruption
Switch among apps and context
Tedious information gathering
Difficult to link to documents and gather pieces of information
39. First Round Observations
Gesture discovery problem
Context preservation & occlusion problem
Recognition problem for out-of-vocabulary word
UIST
List?, Dist?, Gist?, Mist?, Hist?
?
Now we have a basic idea of the system, let me tell you the story behind its design
In the early design stage, we wanted to convince ourselves whether users see values for ink-based search, as well as how they feel about the existing approaches. We conducted a paper prototype studies with 5 researchers.
This is a screenshot a study in progress.
The process goes as follows: they are first asked to write down a page of notes, then comments on if there are terms or phrases they like to search for. The feedback is consistently positive. They all found search for terms and phrase within their notes valuable. We then ask them to perform the search on these terms using an existing desktop search tool called Phlat (which is based on windows desktop search).
Once they have done that, we ask them to propose improvements on the current search interfaces and suggest wanted features. Here are the screen shot of various interfaces proposed during the study.
What we have learned from this study is that, first, existing desktop search tool (which literally designed for desktop computers with keyboard and mice) are very difficult to use. One major problem is that text entry through the tip interface is difficult and tedious.
And it’s annoying to switch between the search application and the active note taking application. Both the tedious text entry process, and the application switches disrupt the train of thoughts, which is very important for active note taking.
Finally, the lack of support of easy gathering and linking the relevant information together in the existing application making the active note taking process inconvenient to deal with.
Based on these findings, we developed a prototype to overcome the forth mentioned limitations, and try to provide an optimal experience for searching while active note taking.
Earlier, we saw the video of how the system works as whole, now I will go through the system step-by-step with you, and discuss the individual features in more details.
The search tool live within an active notebook application, we call it the notebook control (example application are window’s journal or Scriblet)
The application can have a number of objects, and support a number of gestural commands.
Now we have a basic idea of the container application, let’s look at how we can perform the search tasks.
As you can see, we are active note taking on the subject of InkSeine, and trying to gather some related work. We remember there is a paper called Bumptop last year that’s so what interesting, so we want to look it up. To do that, we draw an open ended lasso around the word: BumpTop
Immediately, a small icon appears at the end of the lasso. This icon is called the breadcrumb and it’s an indication that I am interested to perform a search on the selected word. However, I don’t have to dive into the search right away, for example, if my train of thoughts has a number of related work I am thinking about, I can continue write down all the other papers I can think of. The breadcrumb serves as a reminder, information storage, and a placeholder for further actions.
Breadcrumbs provides information about the searches they represent.
By drawing a mark start on the breadcrumb and toward the south, we trigger the personal search, and brings up the search panel
The search panel is composed of different functional units.
On the top, right under the breadcrumb is the query editing and revising area. Since ink can sometimes be mis-interpreted, we need a place to allow the user to correct the ink. Also, user could change their mind and revise the query, the query area also allow the user to add, delete, and edit the query terms.
Once user are sure about their search query, they want to look at the result, which is located right below the query box. It contains multiple columns of information on the research results.
Point to any of the record will make it the focus result with additional information, such as text snippets, thumbnail, and hyperlinks to offer actions for that document.
Based on the lessons we learned from earlier search interfaces such as phlat, two types of filters are the most useful for people to narrow down their search result for personal items. The two types are the file type filter (which is located vertically on the right), and the timeline filter, which is located at the bottom.
Both filters support a number of convenient gestures for pen based interface.
The search panel is composed of different functional units.
When a document opens, we provide the user with a tracking menu to afford pen interaction with legacy mouse-and-keyboard applications. It supports scrolling documents with a scroll ring gesture, and a capture tool for grabbing clippings from a document. The earlier video shows how it works.