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"Moderator: Kevin Ryan, VP, Global Content Director, SES &amp;amp; Search Engine Watch\nSpeakers:\nAmit Kumar, Director Product Management, Yahoo! Search\nNagaraju Bandaru, Co-Founder &amp;amp; CTO, BooRah\nErik Collier, VP, Product Management, Ask.com\nTim McGuiness, VP of Search, hakia.com\nScott Prevost, General Manager &amp;amp; Director of Product, Powerset\nFirst Speaker: Amit Kumar\nMy job today is to convince you that semantic search is coming closer and closer to reality and that you can participate, and I'm planning on exploring the following:\n\n  What does semantic search mean (to us)?\n  Potential user experiences?\n  Let's build it together!\n\nWhat does it mean (to us)? (Understand underlying structured data)\nWhen the web started, most of the content was written by hand. Research papers, personal experiences, etc. Over the last 5 years or so, most of the content (70%+) is coming from structured databases. Search engines and other companies have recognized that getting to and understanding the structured data is of key importance. Once you have access to that data, helping users understand that data is the next step. Help the users get from \u201Cto do\u201D to \u201Cdone\u201D. These are the guiding principles for Yahoo in terms of semantic search.\nPotential User Experiences\n(Amit provides a list of ten sample search queries and then shows samples of Yahoo\u2019s semantic search results \u2013 the results include images, supplemental links below the images, suggestions for further clarifying the query, constraining the query to specific sources, etc.)\nLocal results show maps, yelp reviews, store hours, phone, etc. right in the search results.\nFor the search query util.list, the results show not only relevant results, but it breaks down the results by version of software (cshel: Cool!)\nAll of these results are live today. Some of the things are on by default, including blog results, LinkedIn results, Yelp, etc. It\u2019s providing real value to the users.\nYahoo wants your data. Expose your structured data. Use microformats, RDP markup (preferred). Use datafeeds (based on open RDFa format). Build SearchMonkey applications. In return for going through the trouble to exposure your data, Yahoo is seeing +15% increase in clicks for participating sites.\nNagaraju Bandaru, Co-founder &amp;amp; CTO, BooRah\nBooRah is a local search company that uses natural language processing to extract intention and affinity from user reviews and blogs from across the Internet. BooRah generates that structured data that helps make the semantic search experience richer.\nUltimately, semantic search is about leveraging information to make the content on the semantic search results more relevant.\nGoogle is continue to use \u201Csmart indexing\u201D, keywords/attributes, and behind the scenes semantics. Yahoo is using a more open approach, and is using content markup, open search and integrates vertical data feeds to enhance their results.\nThe companies that are trying to understand the content (more so than just the keywords) are companies like Hakia, Aggregate Knowledge, and BooRah use natural language search, discovery and recommendation, and sentiment analysis.\nDoes search behavior ultimately change the user experience? Bandaru thinks so. When people start searching for \u201CWhere can I find the best fois gras in San Francisco?\u201D and then start getting results that they like and can use, they\u2019ll start doing those types of searches more frequently.\nThis doesn\u2019t negate standard SEO best practices because that is still information that the search engines need, and there are still users who do searches \u201Cold school\u201D.\nBandaru\u2019s company specializes in sentiment extraction to enhance search. Sentiment extraction summarizes \u201Cgobs\u201D of content \u2013 like category specific scores, normalizes different data sources, and then rolls it up into an easy search and sort. They also look at inferred meta data, which leverages existing content like reviews, blogs and message boards. All of this increases relevance and content. It helps filter out keyword spam and also provides more context for location aware mobile applications.\n\nThird Speaker: Erik Collier\nWe believe that the true semantic web is quite a ways away. You will start to see it when you find that you don\u2019t have to rephrase your query to get the results you want. Right now, that\u2019s not the case. The burden is on the user to think the way the engine wants them to think. If the meaning of the query is the same, you should get the same results no matter how you phrase your question. The semantic web will understand your intent and give you the answer based on your intent, not based on the exact arrangement of your keywords.\nTo see examples of how query phrasing and word selection affects the outcome of results, search Google, Yahoo, Live, Ask, Powerset and Hakia with the following queries and note the differences in the results:\nWhat is the population size of Japan?\nWhat is the population of Japan?\nAsk is currently using structured content feeds containing all listings for a 2 wk period. They apply logic based on the actual question (queries for specific actors/titles/etc), and then based on specific words in the search. They then apply user data like location based on IP.\nKevin Ryan asks Eric Collier: So tell me\u2026 we\u2019ve been spending years teaching people to search using caveman speak. How are we going to change the minds of people to get them to switch from the caveman speak to real language search terms?\nErik Collier responds: We\u2019re going to start using a club and hitting them over the head. No really, because Ask.com\u2019s history is using natural language, we feel like we have a leg up on that because we\u2019ve always encouraged our users to ask \u201Creal questions\u201D. We are trying to encourage them by phrasing the suggested query refinements in natural language as well.\nKartal Guner, Chief architect, Hakia.com\nSemantic technology embodies cognitive knowledge and operates on concept relations. It paves the way to text-menaing-representation and conversational aptitude. Challenges:\n\n  Know-how\n  Time constraints/sclability\n\nCurrent web search suffers from the limitations of statistical methods operating on keywords:\n\n  Dependence on link referrals, behavior tracking, corpus selection, etc.\n  Long tail phenomena\n  May be vulnerable to external manipulation (miserable failure)\n\nSemantic Search Operations at Hakia:\n\n  Generalization-Specialization\n  Parallelization (equivalent meanings)\n  Question type detection and relevance \u2013 we\u2019ve broken the standards in about 50 different types.\n  Categorization\n  Compression\n  Content characterization (Qdexing)\n  Disambiguation (applies to all of the above)\n\nAll of these capabilities allow search forms of higher refinement and human interactivity \u2013 conversational search (the user asks questions, the search engine asks questions back to help further refine the query).\nTheir goals are to provide higher relevance for searchers, the freedom to search in natural language and a new search experience \u2013 going beyond 10 blue links, coherent text, focused sentence and referenced links.\nFor advertisers, there\u2019s a higher relevance and better targeting. For SEOs, the goal is to allow them to focus on content rather than keywords.\nScott Prevost, Powerset, General Manager and Director of Product\nWhat we\u2019ve heard from most of the speakers is that semantic search is about structured data, and really most of the data on the web today is still unstructured. So Powerset provides structure to that content.\nKeyword techniques involve shallow representations of document meaning and user intent. Powerset believes that better relevance can be achieved through improved models of the meaning of documents and queries.\nTheir \u201CVision for Search\u201D is two pronged, the first is improving search relevance by applying deep natural language processing to extract semantic features from text and encode them in the index, they also extract semantic features from the queries themselves and then retrieving and ranking documents based on the semantic keywords and other features. The second prong is to improve the user experience.\nThe semantic impact on relevance is improving recall through word and phrase variations (synonyms, hypernyms and anaphors) and improving precision through linguistic structure and content.\nThe impact on the user experience includes allowing more natural and flexible querying \u2013 regardless of whether you\u2019re searching using keywords, topics, phrases, full questions. Powerset also highlights the relevant part of the results for the user.\nLive blogging provided by Cshel.\n\n"^^<http://www.w3.org/2001/XMLSchema#string>
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