..a contextual computing approach may prove a breakthrough in personalized

search efficiency..

Personalized Search

November 2015

Refers to the enhancement of a user’s interactions by understanding the user, the context, and the applications and information being used

It’s about “actively adapting the computational environment - for each and every user - at each point of computation”

“Focuses on understanding the information consumption patterns of each user, the various information foraging strategies and applications they employ, and the nature of the information itself”

A shift from “consensus relevancy” (relevancy for entire population used for every person) to “personal relevancy” (relevancy is determined for each individual)

This shift to personal relevancy decreases the time it takes people to find information

Contextual Computing

Content-based approaches - using language to match a query with results - this approach doesn’t help users determine which results are actually worth reading

Author-relevancy techniques - using citation and hyperlinks - sometimes presents the problem of ‘authoring bias’ and/or ‘ranking bias’ (results that are valued by authors are not necessarily those valued by the entire population)

Usage rank - this “leverages the actions of users to compute relevancy” - the usage rank is computed from the frequency, recency, and/or duration of interaction by users - usage ranks allow for changes in relevancy over time to be determined

All of the above techniques measure relevance “as a function of the entire population of users”

This does not acknowledge that “relevance is relative” for each user

There needs to be a way to “take into account that different people find different things relevant and that people’s interests and knowledge change over time - “personal relevance”

Review of Information Retrieval

In order to personalize search, we need to combine at least two different computational techniques - contextualization and individualization

Contextualization - “the interrelated conditions that occur within an activity..includes factors like the nature of information available, the information currently being examined, and the applications in use”

Individualization - “the totality of characteristics that distinguishes an individual.. Uses the user’s goals, prior and tacit knowledge, past information-seeking behaviors”

The Outride Approach

Main ways to personalize a search are “query augmentation” and “result processing”

Query augmentation - when a user enters a query, the query can be compared against the contextual information available to determine if the query can be refined to include other terms

Query augmentation can also be done by computing the similarity between the query term and the user model - if the query is on a topic the user has previously seen, the system can reinforce the query with similar terms

This more concise query is then shown to the user and “submitted to a search engine for processing”

Once the query has been augmented and processed by the search engine, the results can be “individualized”

The results being individualized - this means that the information is filtered based upon information in the user’s model and/or context

The user model “can re-rank search results based upon the similarity of the content of the pages in the results and the user’s profile”

Another processing method is to re-rank the results based upon the “frequency, recency, or duration of usage..providing users with the ability to identify the most popular, faddish and time-consuming pages they’ve seen”

“Have Seen, Have Not Seen” - this features allows new information to be identified and return to information already seen”

Designed to be a “generalized architecture for the personalization of search across a variety of information ecologies”

The Outride client can be integrated into the sidebar of the Internet - it “supports direct manipulation and has access to all user interactions”

Sidebar is split up into four separate information spaces - Personal (personal hierarchy of each user’s links), Directory (a catalog of links), History (user’s surf history), Web (search results from the entire Web)

The user models are computed from the content in these information spaces in the sidebar

The Outride Personalized Search System

Outride used eTesting Lbs to design a series of test to measure if the Outride system actually succeeded in making searches faster and easier to complete

The elapsed time to successfully complete a search and the number of interface actions (mouse clicks/number of entries entered) were used as the measurements

Participants performed 12 search tasks with Outride and a different search engine

Default user model was used for all participants Participants found the answers more quickly with Outride

than with any other search engine - on average, participants took 39 seconds to complete the tasks using Outride and 75 seconds using Google

Participants also needed fewer interface actions when using Outride - 11 when using Outride and 21 using the other search engine

Testing Methodology and Results

Some of the scenarios contained tasks “directly supported by the functionality provided by the Outride system, creating an advantage against the other search engines”

Default profiles were used, instead of individualized profiles - therefore, it did not “represent the test participant’ actual surfing patterns, nor were the participants intimately familiar with the content of the profiles”

Despite these issues, the “magnitude of the difference between the Outride system and the other engines is compelling”

Issues/problems with the experiments

One problem is modeling a user’s changing interests over time

However, carefully designed interfaces can help “alleviate inaccurate personalization and allow users to control the extent of the personalization”

Privacy issues are a problem since it is a system that stores models based upon user’s interactions with information

Future Directions

“When designing Web personalization products, make sure you address all

your users”By Udi Manber, Ash Patel, and John

Robison

“Experience with Personalization on Yahoo!

This article discusses three different examples of personalization on Yahoo! IncludingMy Yahoo!Yahoo! CompanionInside Yahoo! Search

Overview

My Yahoo! Is a customized personal copy of Yahoo!

Users select from various models such as news, stock prices, weather, and sports scores to put on their Web page.

Provides users with the latest information on every subject, but with only the specific items they want to know about.

My Yahoo!

Personalization Users can do such things as chose certain TV channels to put in their

TV Guide Customized Content

Example of this is a sports module that lists the teams in the user’s area after obtaining that information from the user’s profile.

Automatic Updates A My Yahoo! Option allows this page to automatically update at any

user-specified interval from 15 minutes to several hours Original Module Ability

Modules can be selected from a long list, but can also be added by clicking on a button at the original content page.

Each module on a My Yahoo! Page also has an edit and remove button, allowing users to manipulate their pages directly, without ever needing to visit an edit/layout page.

My Yahoo! Features

A browser’s embedded toolbar from which a user can directly access most of Yahoo! features from anywhere on the Web.

Like a mini My Yahoo! that takes a small space at the top of the page is always with you.

Yahoo! Companion

The user interface is similar to any other bookmark feature, but the difference is the bookmarks are kept on the server (not simply on the specific computer)

Therefore changes that users make to their toolbar will stay with users even if they switch to a different computer

Users have the ability to chose from several toolbars (such as a regular one a stock market one) and change them at any time

Yahoo! Companion Features

Yahoo! like many other search engines tries to personalize searches using information it is able to obtain from the user

It would be impossible for Yahoo! to customize every search.

Inside Yahoo!

If a user searches for the name of current movie, Yahoo will show results for Yahoo! Movies, show an image for the movie, the cast, and a pointer to a page with current show times

If the user had looked at showtimes on a page previously and entered a zip code, Yahoo! can now use that information to show the user movie times in his or her own are

Yahoo! Search Example

Any company that collects private information must guard that information with its life.

Personal information about Yahoo! Is maintained in a specially designed User Database (UDB) which was built on Yahoo!’s own customized software.

Yahoo! has data replication and distribution capabilities allowing them to replicate and distribute the UDB over secure links to remote locations in Asia and Europe

Yahoo! has enlisted a security-audit company to evaluate our procedures periodically and suggest necessary changes, as well as employ several internal people devoted solely to privacy and security issues.

Solving Privacy Problems

The issue of usability focuses mostly on the issue of predictability

Personalization features that learn what user want and attempt to satisfy them are hotly debated

A weakness in these personalization features is unpredictability

Example: A lot of people do not want customized news, they want just the same news as everyone else

Also getting news about cancer because a user some medical journal on cancer in the past can confuse the user and even jeopardize user trust and raise serious privacy concerns in the user’s mind

Any effective personalization feature should encourage experimentation.

User Interface

Most users take what is given to them and never customize.

Even though companies like Yahoo! offer customized pages for users, a great deal of effort must still go into the default page.

Companies should never underestimate power users

Customization should follow you as much as possible

People generally don’t understand the concept of customization

Make sure you address all your usersLearn from users

Observations/Lessons Learned

“Too many attempts have been made without sufficient regard to what people really want, what they can use, and how best it should fit their needs.”

“A major challenge to large-scale personalization is to lower the entry bar, making it easier for less-experienced users to customize their pages, and making it clear to novices that customization is possible.”

Conclusion