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Introduction to Web Search and Advanced Internet Services. Tao Yang UCSB CS290N, Spring 2014. Table of Content. Search Engine Architecture and Process Web Content and Size Users Behavior in Search Sponsored Search: Advertisement Impact to Business and Search Engine Optimization
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Introduction to Web Search and Advanced Internet Services Tao Yang UCSB CS290N, Spring 2014
Table of Content • Search Engine Architecture and Process • Web Content and Size • Users Behavior in Search • Sponsored Search: Advertisement • Impact to Business and Search Engine Optimization • Search engine history and related fields
User Web spider Search Indexer The Web Indexes Ad indexes Web search basics
Search engine architecture: key pieces • Spider (a.k.a. crawler/robot) – builds corpus • Collects web pages recursively • For each known URL, fetch the page, parse it, and extract new URLs • Repeat • Additional pages from direct submissions & other sources • Indexer – creates inverted indexes so online system can search • Online query process– serves query results • Front end – query reformulation, word processing • Back end – finds matching documents and ranks them
Santa Barbara UCSB Dictionary Postings Inverted index • Linked lists generally preferred to arrays • Dynamic space allocation • Insertion of terms into documents easy • Space overhead of pointers 2 4 8 16 32 64 128 1 2 3 5 8 13 21 34 13 16 Sorted by docID (more later on why).
Indexing Process • Text acquisition • identifies and stores documents for indexing • Text transformation • transforms documents into index terms or features • Index creation • takes index terms and creates data structures (indexes) to support fast searching
Crawler Crawler Crawler Parsing Parsing Parsing Indexing and Mining at Ask.com Internet Web documents Document respository Document respository Document respository Inverted index generation Online Database Content classification Link graph generation Spammer removal Duplicate removal Click data analysis
Query Process • User interaction • supports creation and refinement of query, display of results • Ranking • uses query and indexes to generate ranked list of documents • Evaluation • monitors and measures effectiveness and efficiency (primarily offline)
Ranking Ranking Ranking Ranking Ranking Ranking Classification Web page index Ask.com Online Engine Architecture Client queries Traffic load balancer Frontend Frontend Frontend Frontend PageInfo Page Info Hierarchical Cache Neptune Clustering Middleware Cache Cache Cache Document Abstract Web page index Document Abstract Document Abstract Document description Structured DB
User Interaction • Query transformation • Improves initial query, both before and after initial search • Includes text transformation techniques used for documents • Spell checking and query suggestion provide alternatives to original query • Query expansion and relevance feedback modify the original query with additional terms
User Interaction • Results output • Constructs the display of ranked documents for a query • Generates snippets to show how queries match documents • Highlights important words and passages • Retrieves appropriate advertising in many applications • May provide clustering and other visualization tools
Online System Support • Performance optimization • Designing ranking algorithms for efficient processing • Term-at-a time vs. document-at-a-time processing • Safe vs. unsafe optimizations • Distribution • Processing queries in a distributed environment • Query broker distributes queries and assembles results • Caching is a form of distributed searching
Evaluation • Logging • Logging user queries and interaction is crucial for improving search effectiveness and efficiency • Query logs and clickthrough data used for query suggestion, spell checking, query caching, ranking, advertising search, and other components • Ranking analysis • Measuring and tuning ranking effectiveness • Performance analysis • Measuring and tuning system efficiency
General Search vs. Vertical Search • General Search: identify relevant information with a horizontal/exhaustive view of the world. • Vertical Search: • Focus on specific segment of web content • Integrate domain knowledge (e.g. taxonomies /ontology), & deep web • Examples: travel in Expedia, products in Amazon.
Table of Content • Search Engine Architecture and Process • Web Content and Size • Users Behavior in Search • Sponsored Search: Advertisement • Impact to Business and Search Engine Optimization • Search Engine History/Related Fields
The Web Characteristics of Web Content • No design/co-ordination • Distributed content creation, linking • Content includes truth, lies, obsolete information, contradictions … • Structured (databases), semi-structured … • Scale -- huge • Growth – slowed down from initial “volume doubling every few months” • Content can be dynamically generated
AA129 Browser Back-end databases Dynamic Web Content • A page without a static html version • E.g., current status of flight AA129 • Current availability of rooms at a hotel • Usually, assembled at the time of a request from a browser • Typically, URL has a ‘?’ character in it • Most dynamic content is ignored by web spiders • Many reasons including malicious spider traps • Acquired for some content (e.g. news stores) • Application-specific spidering Application server
The web: size • What is being measured? • Number of hosts • Number of (static) html pages • Volume of data • Number of hosts – netcraft survey • http://news.netcraft.com/archives/web_server_survey.html • Gives monthly report on how many web servers are out there • Number of pages – numerous estimates • More to follow later in this course • For a Web engine: how big its index is
Static pages: rate of change • Fetterly et al. study: several views of data, 150 million pages over 11 weekly crawls • Bucketed into 85 groups by extent of change
Diversity • Languages/Encodings • Hundreds (thousands ?) of languages, W3C encodings: 55 (Jul01) [W3C01] • Google (mid 2001): English: 53%, JGCFSKRIP: 30% • Document & query topic Popular Query Topics (from 1 million Google queries, Apr 2000)
Table of Content • Search Engine Architecture and Process • Web Content and Size • Users Behavior in Search • Sponsored Search: Advertisement • Impact to Business and Search Engine Optimization • Search Engine History/Related Fields
The user • Diverse in access methodology • Increasingly, high bandwidth connectivity • Growing segment of mobile users: limitations of form factor – keyboard, display • Diverse in search methodology • Search, search + browse, filter by attribute … • Average query length ~ 2.5 terms • Has to do with what they’re searching for • Poor comprehension of syntax • Early engines surfaced rich syntax – Boolean, phrase, etc. • Current engines hide these
Santa barbara weather Mars surface images Nikon D-SLR Web Search: How do users find content? • Informational (~25%) – want to learn about something • Navigational (~40%) – want to go to that page • Transactional (~35%) – want to do something (web-mediated) • Access a service • Downloads • Shop • Gray areas • Find a good hub • Exploratory search “see what’s there” autism United Airlines Car rental Finland Broder 2002, A Taxomony of web search
Users’ evaluation of engines • Relevance and validity of results • UI – Simple, no clutter, error tolerant • Trust – Results are objective, the engine wants to help me • Pre/Post process tools provided • Mitigate user errors (auto spell check) • Explicit: Search within results, more like this, refine ... • Anticipative: related searches
Users’ evaluation • Quality of pages varies widely • Relevance is not enough • Duplicate elimination • Precision vs. recall • On the web, recall seldom matters • What matters • Precision at 1? Precision above the fold? • Comprehensiveness – must be able to deal with obscure queries • Recall matters when the number of matches is very small • User perceptions may be unscientific, but are significant over a large aggregate
What about on Mobile • Query characteristics: • Best known studies by Kamvar and Baluja (2006 and 2007) and by Yi, Maghoul, and Pedersen (2008) • Have a different distribution than the query distribution for PC users • Bias towards shorter queries • Data contradicts that: 2.6 words per query, same # chars as PC • Difficulty of query entry is a significant hurdle • Much higher location-based activity • More notification-driven tasks
Implications and Challenges • Task-orientation • Specialized content packaging • Locality Inference from queries and from devices • Minimize typing and round-trips: get results, not just links • Less room to display SERP + other accessories • Use of mobile in social settings and leveraging notification abilities
Table of Content • Search Engine Architecture and Process • Web Content and Size • Users Behavior in Search • Sponsored Search: Advertisement • Impact to Business and Search Engine Optimization
Search query Ad
Questions • Do you think an “average” user, knows the difference between sponsored search links and algorithmic search results?
I want to bid $5 on canon camera I want to bid $2 on cannon camera How it works Ad Index Advertiser Sponsored search engine Engine decides when/where to show this ad. Landing page Engine decides how much to charge advertiser on a click.
IR Econ Three sub-problems • Match ads to query/context • Order the ads • Pricing on a click-through
Paid placement • Gives consumer opportunity to click through to an advertiser • Compensated by advertiser for click through • Each consumer reveals clues about her information need at hand • The keyword(s) he types (e.g., miele) • Keyword(s) in his email (gmail) • Personal profile information (Yahoo! …) • Complex logistical problems: selling contracts, scheduling ads – supply chain optimization
Table of Content • Search Engine Architecture and Process • Web Content and Size • Users Behavior in Search • Sponsored Search: Advertisement • Impact to Business and Search Engine Optimization • Search Engine History/Related Fields
Search Traffic is Important for Business: Example of Site Traffic Analysis
The trouble with paid placement • It costs money. What’s the alternative? • Search Engine Optimization: • “Tuning” your web page to rank highly in the search results for select keywords • Alternative to paying for placement • Thus, intrinsically a marketing function • Also known as Search Engine Marketing • Performed by companies, webmasters and consultants (“Search engine optimizers”) for their clients
Search engine optimization • Motives • Commercial, political, religious, lobbies • Promotion funded by advertising budget • Operators • Contractors (Search Engine Optimizers) for lobbies, companies • Web masters • Hosting services • Forum • Web master world ( www.webmasterworld.com ) • Search engine specific tricks • Discussions about academic papers • More pointers in the Resources
Simplest forms • Early engines relied on the density of terms • The top-ranked pages for the query maui resort were the ones containing the most maui’s and resort’s • SEOs responded with dense repetitions of chosen terms • e.g., maui resort maui resort maui resort • Often, the repetitions would be in the same color as the background of the web page • Repeated terms got indexed by crawlers • But not visible to humans on browsers Can’t trust the words on a web page, for ranking.
Invisible text auctions.hitsoffice.com/ Pornographic Content
Link Farms Boost pagerank of a website
Table of Content • Search Engine Architecture and Process • Web Content and Size • Users Behavior in Search • Sponsored Search: Advertisement • Impact to Business and Search Engine Optimization • Search Engine History/Related Fields