BSNL Telecom service provider, India has come out with Help Line to locate those who were left stranded by the recent Uttarakhand Floods.
BSNL has established a Help Line Number ,” for getting last mobile location update in Uttarakhand. No is 1503 or 09412024365,” BSNL CMD R K Upadhyay said.
This will help people find out the last mobile phone location of their relatives and friends stranded in flood-hit Uttarakhand.
Related:
Please use this to find persons missing.
Currently tracking about 15000 records.
You can request status via SMS by sending an SMS to 9 77 33 00 000with the message Search person-name.
For example, if you are searching for Jayanth, send the messageSearch (more…)
As one keeps on Blogging,one would like to know as to how his blog is read,number of people per Day/Month;how many pages are viewed,how much time the reader spends on the site ,what the bounce rate is and a host of other details like keywords .
There are number of sites providing this information free of cost.
I have found Alexa.com the easiest to understand without too many IT jargon,simple yet detailed.
You visit the site ,enter you site url in Search and you get information on Traffic Rank(Global and Country specific, Reach,Page views,Page Views/user,Bounce Rate,Time on spent on site ans Search information relating to your site.
You can also get information on audience profile,age,income group,educational level and keywords details.
You would also get to know how your site looked in the past by way back machine.
You also get to know details on in bound links and outward links apart from the details of sites linking to your site.
You may become a member by creating an account and the site has affiliates programme as well.
Loading time is provided and you can correct mistakes,adjust your blog accordingly.
The only disadvantage I felt was that it does not provide historical data for anything ,1,00,00.
You get Click stream, Related Links and a host of other details relating to your site.
There are two kinds of Bloggers,who write for their pleasure and for the Audience.
I belong to the first category.
But as one goes along he finds that a section of the audience like what he writes and with the help of Alexa he can zero in on the group,key words,subjects and concentrate on those topics/tags.
More than others it was a revelation to me as I write what ever that interests me and I have found that there are people who have the same predicament,in my case as to what I really write consistently on and for others what they really are interested in reading.
I find in Alexa a good friend who does not preach.
For bloggers, I have always maintained that the content must be interesting,supported by facts/links and the posts are to be educative,informative and interesting.
The blogger should be interested and believe in what he/she writes.
One need not bother about as to how some body ranks, unless of course you write for money.
Google on Monday revealed 10 recent changes to its search algorithm that affect results as diverse as those that are date-specific and those that are in Hindi.
Google makes more than 500 changes to its search algorithm each year. Most are tiny and some — including a recent one that added real-time results for a third of search queries — affect a large proportion of searches.
But Google rarely publicizes its algorithm changes. One reason: It does not want to give hints to the Web sites that try to game the algorithm so that their links show up higher in results. Google chose to reveal these changes because they are less susceptible to gaming, Matt Cutts, a distinguished engineer at Google who works on search quality, wrote in a company blog post.
There is also another reason that Google is shedding some light on the black box of its algorithm. It is under fire from government regulators who are investigating it for antitrust violations. One of their main concerns is how little Google reveals about how search works, even though changes in the algorithm can drastically affect Web businesses.
One of the new changes will affect searches in languages for which there is little Web content available, including Afrikaans, Hindi and Icelandic. Google will now translate relevant Web pages written in English and show those results, too.
Today we’re continuing our long-standing series of blog posts to share the methodology and process behind our search ranking, evaluation and algorithmic changes. This summer we published a video that gives a glimpse into our overall process, and today we want to give you a flavor of specific algorithm changes by publishing a highlight list of many of the improvements we’ve made over the past couple weeks.
We’ve published hundreds of blog posts about search over the years on this blog, our Official Google Blog, and even on my personal blog. But we’re always looking for ways to give you even deeper insight into the over 500 changes we make to search in a given year. In that spirit, here’s a list of ten improvements from the past couple weeks:
Cross-language information retrieval updates: For queries in languages where limited web content is available (Afrikaans, Malay, Slovak, Swahili, Hindi, Norwegian, Serbian, Catalan, Maltese, Macedonian, Albanian, Slovenian, Welsh, Icelandic), we will now translate relevant English web pages and display the translated titles directly below the English titles in the search results. This feature was available previously in Korean, but only at the bottom of the page. Clicking on the translated titles will take you to pages translated from English into the query language.
Snippets with more page content and less header/menu content: This change helps us choose more relevant text to use in snippets. As we improve our understanding of web page structure, we are now more likely to pick text from the actual page content, and less likely to use text that is part of a header or menu.
Better page titles in search results by de-duplicating boilerplate anchors: We look at a number of signals when generating a page’s title. One signal is the anchor text in links pointing to the page. We found that boilerplate links with duplicated anchor text are not as relevant, so we are putting less emphasis on these. The result is more relevant titles that are specific to the page’s content.
Length-based autocomplete predictions in Russian: This improvement reduces the number of long, sometimes arbitrary query predictions in Russian. We will not make predictions that are very long in comparison either to the partial query or to the other predictions for that partial query. This is already our practice in English.
Extending application rich snippets: We recently announced rich snippets for applications. This enables people who are searching for software applications to see details, like cost and user reviews, within their search results. This change extends the coverage of application rich snippets, so they will be available more often.
Retiring a signal in Image search: As the web evolves, we often revisit signals that we launched in the past that no longer appear to have a significant impact. In this case, we decided to retire a signal in Image Search related to images that had references from multiple documents on the web.
Fresher, more recent results: As we announced just over a week ago, we’ve made a significant improvement to how we rank fresh content. This change impacts roughly 35 percent of total searches (around 6-10% of search results to a noticeable degree) and better determines the appropriate level of freshness for a given query.
Refining official page detection: We try hard to give our users the most relevant and authoritative results. With this change, we adjusted how we attempt to determine which pages are official. This will tend to rank official websites even higher in our ranking.
Improvements to date-restricted queries: We changed how we handle result freshness for queries where a user has chosen a specific date range. This helps ensure that users get the results that are most relevant for the date range that they specify.
Prediction fix for IME queries: This change improves how Autocomplete handles IME queries (queries which contain non-Latin characters). Autocomplete was previously storing the intermediate keystrokes needed to type each character, which would sometimes result in gibberish predictions for Hebrew, Russian and Arabic.
Search terms can be parsed in a similar fashion. Every searcher can be defined by the words they use when searching. Search engines and marketers alike know this and do their best to deliver you relevant results based on who they think you are and your intent at that exact moment.
As an extension of the targeting by intent strategy, a sophisticated and growing segment of brands are turning to searcher demographics to conduct detailed analyses of their online audience. There are already lots of opportunities for marketers to customize their messaging, placement, landing pages, and the like, for every consumer segment, but the brand managers out there have been using search terms to actually identify the attributes of a “Coke” vs. a “Pepsi” searcher. Considering the money that is spent on brand advertising, knowing how your branded search audience differs from that of the competition should be a valuable nugget of information.
To illustrate the point, below are some fun and interesting universal brand identities with dichotomous stances. Each example analyzes the demographics of searchers that used the branded terms for the month of July, and are based on head of household. The index baselines are the searcher demographics for the entire US search population. Available measures are Age, Income, Location (home/work), Region of the US, Household Size, and Presence of Children in the Household….
The most striking differences between Google+ searchers and Facebook searchers are in Age and Income level. Google+ searchers overwhelmingly skew towards 18-34 year olds. Clearly Google+ is a popular brand with the younger segments, and good knowledge for Google to have as they develop their acquisition strategy and evolve their user base. Since Facebook is a much more mature brand in the social networking space, their search audience falls closely in line with the search population at large.
The income skews are even more distinct, essentially polar opposites of each other. More than 32% of Google+ searchers have a household income of $100K or greater, compared to 23% of Facebook searchers. Google+ is definitely off to a fast start in reaching the most desirable income segments, which may make it more attractive to advertisers.
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